Assignment 4

covid <- read.csv("Corona_NLP_train.csv")

library(qdap)
covid$OriginalTweet = rm_stopwords(covid$OriginalTweet, stopwords = tm::stopwords("english"), separate = FALSE, strip = TRUE)
covid$OriginalTweet = stemmer(covid$OriginalTweet, warn = FALSE)

2. Randomize order of rows, use same seed.

set.seed(1)
shuffle_covid <- covid[sample(nrow(covid), replace = FALSE),]
str(covid)

'data.frame':   41157 obs. of  6 variables:
 $ UserName     : int  3799 3800 3801 3802 3803 3804 3805 3806 3807 3808 ...
 $ ScreenName   : int  48751 48752 48753 48754 48755 48756 48757 48758 48759 48760 ...
 $ Location     : chr  "London" "UK" "Vagabonds" "" ...
 $ TweetAt      : chr  "16-03-2020" "16-03-2020" "16-03-2020" "16-03-2020" ...
 $ OriginalTweet: chr  "Menyrbi philgahan chrisitv httpstcoifz fan pa httpstcoxx ghgfzcc httpstcoi nlzdxno" "Advic talk neighbour famili exchang phone number creat contact list phone number neighbour school employ chemis"| __truncated__ "Coronavirus australia woolworth give elder disabl dedic shop hour amid covid outbreak httpstcobinca vp p" "Food stock one empti pleas panic will enough food everyon take need stay calm stay safe covid franc covid covid"| __truncated__ ...
 $ Sentiment    : chr  "Neutral" "Positive" "Positive" "Positive" ...

3. Convert sentiment into a factor variable with 3 levels: positive, negative, and neutral. Then convert factor variable into a numeric vector.

shuffle_covid$Sentiment <- factor(shuffle_covid$Sentiment)
levels(shuffle_covid$Sentiment)[levels(shuffle_covid$Sentiment) == "Extremely Negative"] <- "Negative"
levels(shuffle_covid$Sentiment)[levels(shuffle_covid$Sentiment) == "Extremely Positive"] <- "Positive"
shuffle_covid$Sentiment <-as.numeric(shuffle_covid[,"Sentiment"])-1

4. Split the data in to train/validation/test as follows : first 26340 rows for training, 6585 rows for validation, and 8232 rows for testing.

covid_train <- shuffle_covid[1:26340,]
covid_valid <- shuffle_covid[26340:32925,]
covid_test <- shuffle_covid[32926:41157,]

5. Use the following code segment to create document-term matrix for training, validation, and test datasets.

library(keras)
text_vectorizer <- layer_text_vectorization(output_mode = "tf_idf", ngrams = 2, max_tokens = 5000)
text_vectorizer %>% adapt(covid_train$OriginalTweet)

covid_train_dtm = text_vectorizer(covid_train$OriginalTweet)
covid_valid_dtm = text_vectorizer(covid_valid$OriginalTweet)

WARNING:tensorflow:Tensor._shape is private, use Tensor.shape instead. Tensor._shape will eventually be removed.
WARNING:tensorflow:Tensor._shape is private, use Tensor.shape instead. Tensor._shape will eventually be removed.

covid_test_dtm = text_vectorizer(covid_test$OriginalTweet)

Q1. Create an ANN model with 2 hidden layers to classify tweets into 3 classes.

model = keras_model_sequential()

model %>%
  layer_dense(units = 40, activation = "relu", input_shape = 5000) %>%
  layer_dense(units = 20, activation = "relu") %>%
  layer_dense(units = 3, activation = "softmax")

model %>% compile(
  optimizer = 'adam',
  loss = 'sparse_categorical_crossentropy',
  metrics = c('accuracy')
)

set.seed(1)


model %>% fit(
  covid_train_dtm,covid_train$Sentiment, epochs = 30, batch_size = 100, validation_data = list(covid_valid_dtm,covid_valid$Sentiment)
)

Epoch 1/30

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264/264 [==============================] - 6s 18ms/step - loss: 0.7717 - accuracy: 0.6654

264/264 [==============================] - 6s 21ms/step - loss: 0.7717 - accuracy: 0.6654 - val_loss: 0.6415 - val_accuracy: 0.7435
Epoch 2/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.5121 - accuracy: 0.8101

264/264 [==============================] - 2s 6ms/step - loss: 0.5121 - accuracy: 0.8101 - val_loss: 0.6318 - val_accuracy: 0.7502
Epoch 3/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.4032 - accuracy: 0.8544 - val_loss: 0.6585 - val_accuracy: 0.7442
Epoch 4/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.3112 - accuracy: 0.8866 - val_loss: 0.7164 - val_accuracy: 0.7511
Epoch 5/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.2225 - accuracy: 0.9222 - val_loss: 0.8399 - val_accuracy: 0.7448
Epoch 6/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.1436 - accuracy: 0.9539 - val_loss: 0.9498 - val_accuracy: 0.7326
Epoch 7/30

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Epoch 8/30

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Epoch 9/30

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Epoch 10/30

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Epoch 11/30

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Epoch 12/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0120 - accuracy: 0.9976 - val_loss: 1.8159 - val_accuracy: 0.7281
Epoch 13/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0097 - accuracy: 0.9984 - val_loss: 1.9358 - val_accuracy: 0.7258
Epoch 14/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0085 - accuracy: 0.9984 - val_loss: 1.9678 - val_accuracy: 0.7237
Epoch 15/30

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264/264 [==============================] - 0s 2ms/step - loss: 0.0220 - accuracy: 0.9939

264/264 [==============================] - 1s 3ms/step - loss: 0.0220 - accuracy: 0.9939 - val_loss: 1.9734 - val_accuracy: 0.7165
Epoch 16/30

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264/264 [==============================] - 1s 2ms/step - loss: 0.0689 - accuracy: 0.9762

264/264 [==============================] - 1s 3ms/step - loss: 0.0689 - accuracy: 0.9762 - val_loss: 1.9124 - val_accuracy: 0.7152
Epoch 17/30

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264/264 [==============================] - 0s 2ms/step - loss: 0.0493 - accuracy: 0.9852

264/264 [==============================] - 1s 3ms/step - loss: 0.0493 - accuracy: 0.9852 - val_loss: 1.9695 - val_accuracy: 0.7115
Epoch 18/30

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264/264 [==============================] - 0s 2ms/step - loss: 0.0208 - accuracy: 0.9941

264/264 [==============================] - 1s 3ms/step - loss: 0.0208 - accuracy: 0.9941 - val_loss: 2.0295 - val_accuracy: 0.7243
Epoch 19/30

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264/264 [==============================] - 0s 2ms/step - loss: 0.0073 - accuracy: 0.9987

264/264 [==============================] - 1s 3ms/step - loss: 0.0073 - accuracy: 0.9987 - val_loss: 2.0943 - val_accuracy: 0.7221
Epoch 20/30

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264/264 [==============================] - 0s 2ms/step - loss: 0.0053 - accuracy: 0.9992

264/264 [==============================] - 1s 3ms/step - loss: 0.0053 - accuracy: 0.9992 - val_loss: 2.2015 - val_accuracy: 0.7237
Epoch 21/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0031 - accuracy: 0.9994 - val_loss: 2.2511 - val_accuracy: 0.7246
Epoch 22/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0024 - accuracy: 0.9995 - val_loss: 2.3223 - val_accuracy: 0.7258
Epoch 23/30

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264/264 [==============================] - 0s 2ms/step - loss: 0.0026 - accuracy: 0.9994

264/264 [==============================] - 1s 3ms/step - loss: 0.0026 - accuracy: 0.9994 - val_loss: 2.3507 - val_accuracy: 0.7247
Epoch 24/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0025 - accuracy: 0.9995 - val_loss: 2.3703 - val_accuracy: 0.7238
Epoch 25/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0024 - accuracy: 0.9993 - val_loss: 2.4391 - val_accuracy: 0.7300
Epoch 26/30

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264/264 [==============================] - 1s 2ms/step - loss: 0.0044 - accuracy: 0.9989

264/264 [==============================] - 1s 3ms/step - loss: 0.0044 - accuracy: 0.9989 - val_loss: 2.4448 - val_accuracy: 0.7209
Epoch 27/30

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264/264 [==============================] - 0s 2ms/step - loss: 0.0155 - accuracy: 0.9954

264/264 [==============================] - 1s 3ms/step - loss: 0.0155 - accuracy: 0.9954 - val_loss: 2.3247 - val_accuracy: 0.7158
Epoch 28/30

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264/264 [==============================] - 0s 2ms/step - loss: 0.0402 - accuracy: 0.9884

264/264 [==============================] - 1s 3ms/step - loss: 0.0402 - accuracy: 0.9884 - val_loss: 2.2933 - val_accuracy: 0.7194
Epoch 29/30

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264/264 [==============================] - 1s 2ms/step - loss: 0.0256 - accuracy: 0.9922

264/264 [==============================] - 1s 3ms/step - loss: 0.0256 - accuracy: 0.9922 - val_loss: 2.3840 - val_accuracy: 0.7173
Epoch 30/30

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264/264 [==============================] - 0s 2ms/step - loss: 0.0105 - accuracy: 0.9978

264/264 [==============================] - 1s 3ms/step - loss: 0.0105 - accuracy: 0.9978 - val_loss: 2.3944 - val_accuracy: 0.7217

library(gmodels)
predicted_labels = as.numeric(model %>% predict(covid_test_dtm) %>% k_argmax())

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258/258 [==============================] - 0s 584us/step

258/258 [==============================] - 0s 588us/step

CrossTable(predicted_labels,covid_test$Sentiment, prop.chisq = FALSE, prop.t = FALSE, dnn = c('predicted','actual'))

 
   Cell Contents
|-------------------------|
|                       N |
|           N / Row Total |
|           N / Col Total |
|-------------------------|

 
Total Observations in Table:  8232 

 
             | actual 
   predicted |         0 |         1 |         2 | Row Total | 
-------------|-----------|-----------|-----------|-----------|
           0 |      2317 |       508 |       345 |      3170 | 
             |     0.731 |     0.160 |     0.109 |     0.385 | 
             |     0.752 |     0.141 |     0.222 |           | 
-------------|-----------|-----------|-----------|-----------|
           1 |       539 |      2895 |       394 |      3828 | 
             |     0.141 |     0.756 |     0.103 |     0.465 | 
             |     0.175 |     0.805 |     0.253 |           | 
-------------|-----------|-----------|-----------|-----------|
           2 |       225 |       192 |       817 |      1234 | 
             |     0.182 |     0.156 |     0.662 |     0.150 | 
             |     0.073 |     0.053 |     0.525 |           | 
-------------|-----------|-----------|-----------|-----------|
Column Total |      3081 |      3595 |      1556 |      8232 | 
             |     0.374 |     0.437 |     0.189 |           | 
-------------|-----------|-----------|-----------|-----------|

 

From the table, the model had a total of 2203 mistakes, with a total error rate of 26%. For ‘0’, the model had predicted 73.1% correctly, ‘1’ had 75.6%, and ‘2’ had 66.2%.

Q2 Use “tfruns” package to tune ANN’s hyper-parametesr including number of nodes in each layer, batch_size, and learning_rate. Validate each model on the validation set.

library(tfruns)



runs <- tuning_run("Corona_NLP_train.R",
                   flags = list(
                     nodes = c(64, 128, 392),
                     learning_rate = c(0.01, 0.05, 0.001, 0.0001),
                     batch_size= c(100, 200, 500, 1000),
                     epochs = c(30,50,100),
                     activation = c("relu", "sigmoid", "tanh")
                   ),
                   sample = 0.02
)

432 total combinations of flags 
(sampled to 9 combinations)

Y

Training run 1/9 (flags = list(64, 0.01, 500, 50, "sigmoid")) 
Using run directory runs/2023-03-31T02-03-48Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 5000) %>%
+   layer_dense(units = FLAGS$nodes, activatio .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('accuracy .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   covid_train_dtm,covid_train$Sentiment, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(covid_valid_d .... [TRUNCATED] 
Epoch 1/50

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53/53 [==============================] - 1s 6ms/step - loss: 0.9918 - accuracy: 0.5083

53/53 [==============================] - 1s 19ms/step - loss: 0.9918 - accuracy: 0.5083 - val_loss: 0.8846 - val_accuracy: 0.6089
Epoch 2/50

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53/53 [==============================] - 0s 7ms/step - loss: 0.7282 - accuracy: 0.7295

53/53 [==============================] - 1s 10ms/step - loss: 0.7282 - accuracy: 0.7295 - val_loss: 0.6714 - val_accuracy: 0.7299
Epoch 3/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.5217 - accuracy: 0.8205

53/53 [==============================] - 0s 9ms/step - loss: 0.5217 - accuracy: 0.8205 - val_loss: 0.6045 - val_accuracy: 0.7586
Epoch 4/50

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53/53 [==============================] - 0s 5ms/step - loss: 0.4286 - accuracy: 0.8548

53/53 [==============================] - 0s 9ms/step - loss: 0.4286 - accuracy: 0.8548 - val_loss: 0.6067 - val_accuracy: 0.7610
Epoch 5/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.3810 - accuracy: 0.8729

53/53 [==============================] - 0s 9ms/step - loss: 0.3810 - accuracy: 0.8729 - val_loss: 0.6235 - val_accuracy: 0.7639
Epoch 6/50

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53/53 [==============================] - 0s 5ms/step - loss: 0.3482 - accuracy: 0.8845

53/53 [==============================] - 0s 9ms/step - loss: 0.3482 - accuracy: 0.8845 - val_loss: 0.6364 - val_accuracy: 0.7621
Epoch 7/50

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53/53 [==============================] - 0s 5ms/step - loss: 0.3245 - accuracy: 0.8946

53/53 [==============================] - 0s 9ms/step - loss: 0.3245 - accuracy: 0.8946 - val_loss: 0.6583 - val_accuracy: 0.7601
Epoch 8/50

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53/53 [==============================] - 0s 5ms/step - loss: 0.3027 - accuracy: 0.9028

53/53 [==============================] - 0s 9ms/step - loss: 0.3027 - accuracy: 0.9028 - val_loss: 0.6880 - val_accuracy: 0.7558
Epoch 9/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.2826 - accuracy: 0.9107

53/53 [==============================] - 0s 9ms/step - loss: 0.2826 - accuracy: 0.9107 - val_loss: 0.7107 - val_accuracy: 0.7565
Epoch 10/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.2622 - accuracy: 0.9181

53/53 [==============================] - 1s 10ms/step - loss: 0.2622 - accuracy: 0.9181 - val_loss: 0.7368 - val_accuracy: 0.7528
Epoch 11/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.2455 - accuracy: 0.9253

53/53 [==============================] - 1s 10ms/step - loss: 0.2455 - accuracy: 0.9253 - val_loss: 0.7620 - val_accuracy: 0.7519
Epoch 12/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.2253 - accuracy: 0.9344

53/53 [==============================] - 0s 9ms/step - loss: 0.2253 - accuracy: 0.9344 - val_loss: 0.7925 - val_accuracy: 0.7502
Epoch 13/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.2081 - accuracy: 0.9402

53/53 [==============================] - 1s 10ms/step - loss: 0.2081 - accuracy: 0.9402 - val_loss: 0.8196 - val_accuracy: 0.7516
Epoch 14/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.1884 - accuracy: 0.9485

53/53 [==============================] - 0s 9ms/step - loss: 0.1884 - accuracy: 0.9485 - val_loss: 0.8514 - val_accuracy: 0.7463
Epoch 15/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.1700 - accuracy: 0.9550

53/53 [==============================] - 1s 10ms/step - loss: 0.1700 - accuracy: 0.9550 - val_loss: 0.8849 - val_accuracy: 0.7455
Epoch 16/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.1525 - accuracy: 0.9612

53/53 [==============================] - 1s 10ms/step - loss: 0.1525 - accuracy: 0.9612 - val_loss: 0.9228 - val_accuracy: 0.7449
Epoch 17/50

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53/53 [==============================] - 0s 5ms/step - loss: 0.1348 - accuracy: 0.9691

53/53 [==============================] - 0s 9ms/step - loss: 0.1348 - accuracy: 0.9691 - val_loss: 0.9575 - val_accuracy: 0.7446
Epoch 18/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.1176 - accuracy: 0.9743

53/53 [==============================] - 0s 9ms/step - loss: 0.1176 - accuracy: 0.9743 - val_loss: 1.0022 - val_accuracy: 0.7440
Epoch 19/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.1033 - accuracy: 0.9792

53/53 [==============================] - 0s 9ms/step - loss: 0.1033 - accuracy: 0.9792 - val_loss: 1.0389 - val_accuracy: 0.7426
Epoch 20/50

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53/53 [==============================] - 0s 7ms/step - loss: 0.0887 - accuracy: 0.9827

53/53 [==============================] - 1s 11ms/step - loss: 0.0887 - accuracy: 0.9827 - val_loss: 1.0751 - val_accuracy: 0.7434
Epoch 21/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0772 - accuracy: 0.9859

53/53 [==============================] - 1s 10ms/step - loss: 0.0772 - accuracy: 0.9859 - val_loss: 1.1162 - val_accuracy: 0.7420
Epoch 22/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0657 - accuracy: 0.9885

53/53 [==============================] - 1s 10ms/step - loss: 0.0657 - accuracy: 0.9885 - val_loss: 1.1576 - val_accuracy: 0.7425
Epoch 23/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0564 - accuracy: 0.9909

53/53 [==============================] - 1s 10ms/step - loss: 0.0564 - accuracy: 0.9909 - val_loss: 1.1967 - val_accuracy: 0.7411
Epoch 24/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0487 - accuracy: 0.9922

53/53 [==============================] - 0s 9ms/step - loss: 0.0487 - accuracy: 0.9922 - val_loss: 1.2346 - val_accuracy: 0.7402
Epoch 25/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0419 - accuracy: 0.9938

53/53 [==============================] - 1s 11ms/step - loss: 0.0419 - accuracy: 0.9938 - val_loss: 1.2882 - val_accuracy: 0.7378
Epoch 26/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0366 - accuracy: 0.9951

53/53 [==============================] - 1s 10ms/step - loss: 0.0366 - accuracy: 0.9951 - val_loss: 1.3093 - val_accuracy: 0.7384
Epoch 27/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0316 - accuracy: 0.9959

53/53 [==============================] - 1s 10ms/step - loss: 0.0316 - accuracy: 0.9959 - val_loss: 1.3426 - val_accuracy: 0.7396
Epoch 28/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0272 - accuracy: 0.9967

53/53 [==============================] - 1s 10ms/step - loss: 0.0272 - accuracy: 0.9967 - val_loss: 1.3837 - val_accuracy: 0.7366
Epoch 29/50

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53/53 [==============================] - 0s 7ms/step - loss: 0.0236 - accuracy: 0.9971

53/53 [==============================] - 1s 10ms/step - loss: 0.0236 - accuracy: 0.9971 - val_loss: 1.4202 - val_accuracy: 0.7355
Epoch 30/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0207 - accuracy: 0.9975

53/53 [==============================] - 1s 10ms/step - loss: 0.0207 - accuracy: 0.9975 - val_loss: 1.4469 - val_accuracy: 0.7347
Epoch 31/50

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53/53 [==============================] - 0s 5ms/step - loss: 0.0184 - accuracy: 0.9978

53/53 [==============================] - 0s 9ms/step - loss: 0.0184 - accuracy: 0.9978 - val_loss: 1.4810 - val_accuracy: 0.7337
Epoch 32/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0164 - accuracy: 0.9983

53/53 [==============================] - 0s 9ms/step - loss: 0.0164 - accuracy: 0.9983 - val_loss: 1.5062 - val_accuracy: 0.7332
Epoch 33/50

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53/53 [==============================] - 0s 9ms/step - loss: 0.0146 - accuracy: 0.9985 - val_loss: 1.5337 - val_accuracy: 0.7334
Epoch 34/50

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53/53 [==============================] - 0s 7ms/step - loss: 0.0136 - accuracy: 0.9987

53/53 [==============================] - 1s 11ms/step - loss: 0.0136 - accuracy: 0.9987 - val_loss: 1.5609 - val_accuracy: 0.7300
Epoch 35/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0118 - accuracy: 0.9988

53/53 [==============================] - 1s 12ms/step - loss: 0.0118 - accuracy: 0.9988 - val_loss: 1.5884 - val_accuracy: 0.7293
Epoch 36/50

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53/53 [==============================] - 1s 10ms/step - loss: 0.0108 - accuracy: 0.9989 - val_loss: 1.6085 - val_accuracy: 0.7314
Epoch 37/50

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53/53 [==============================] - 1s 10ms/step - loss: 0.0100 - accuracy: 0.9990 - val_loss: 1.6358 - val_accuracy: 0.7303
Epoch 38/50

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53/53 [==============================] - 1s 10ms/step - loss: 0.0088 - accuracy: 0.9990 - val_loss: 1.6561 - val_accuracy: 0.7284
Epoch 39/50

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53/53 [==============================] - 1s 10ms/step - loss: 0.0079 - accuracy: 0.9991 - val_loss: 1.6775 - val_accuracy: 0.7325
Epoch 40/50

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53/53 [==============================] - 1s 11ms/step - loss: 0.0073 - accuracy: 0.9991 - val_loss: 1.7023 - val_accuracy: 0.7279
Epoch 41/50

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53/53 [==============================] - 1s 10ms/step - loss: 0.0066 - accuracy: 0.9993 - val_loss: 1.7185 - val_accuracy: 0.7312
Epoch 42/50

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53/53 [==============================] - 1s 11ms/step - loss: 0.0060 - accuracy: 0.9995 - val_loss: 1.7363 - val_accuracy: 0.7285
Epoch 43/50

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53/53 [==============================] - 1s 11ms/step - loss: 0.0056 - accuracy: 0.9995 - val_loss: 1.7539 - val_accuracy: 0.7293
Epoch 44/50

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53/53 [==============================] - 0s 9ms/step - loss: 0.0053 - accuracy: 0.9995 - val_loss: 1.7718 - val_accuracy: 0.7293
Epoch 45/50

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53/53 [==============================] - 1s 10ms/step - loss: 0.0051 - accuracy: 0.9995 - val_loss: 1.7923 - val_accuracy: 0.7278
Epoch 46/50

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53/53 [==============================] - 0s 9ms/step - loss: 0.0049 - accuracy: 0.9995 - val_loss: 1.8038 - val_accuracy: 0.7303
Epoch 47/50

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53/53 [==============================] - 0s 9ms/step - loss: 0.0045 - accuracy: 0.9996 - val_loss: 1.8195 - val_accuracy: 0.7297
Epoch 48/50

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53/53 [==============================] - 0s 9ms/step - loss: 0.0044 - accuracy: 0.9994 - val_loss: 1.8313 - val_accuracy: 0.7293
Epoch 49/50

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53/53 [==============================] - 0s 6ms/step - loss: 0.0042 - accuracy: 0.9996

53/53 [==============================] - 1s 10ms/step - loss: 0.0042 - accuracy: 0.9996 - val_loss: 1.8440 - val_accuracy: 0.7297
Epoch 50/50

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53/53 [==============================] - 0s 9ms/step - loss: 0.0043 - accuracy: 0.9995 - val_loss: 1.8667 - val_accuracy: 0.7271

Run completed: runs/2023-03-31T02-03-48Z

Training run 2/9 (flags = list(392, 0.05, 500, 50, "tanh")) 
Using run directory runs/2023-03-31T02-04-15Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 5000) %>%
+   layer_dense(units = FLAGS$nodes, activatio .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('accuracy .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   covid_train_dtm,covid_train$Sentiment, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(covid_valid_d .... [TRUNCATED] 
Epoch 1/50

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53/53 [==============================] - 1s 20ms/step - loss: 0.9916 - accuracy: 0.5696

53/53 [==============================] - 2s 34ms/step - loss: 0.9916 - accuracy: 0.5696 - val_loss: 0.6641 - val_accuracy: 0.7246
Epoch 2/50

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53/53 [==============================] - 1s 20ms/step - loss: 0.4855 - accuracy: 0.8177

53/53 [==============================] - 1s 25ms/step - loss: 0.4855 - accuracy: 0.8177 - val_loss: 0.6269 - val_accuracy: 0.7539
Epoch 3/50

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53/53 [==============================] - 1s 21ms/step - loss: 0.3462 - accuracy: 0.8772

53/53 [==============================] - 1s 26ms/step - loss: 0.3462 - accuracy: 0.8772 - val_loss: 0.6825 - val_accuracy: 0.7463
Epoch 4/50

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53/53 [==============================] - 1s 21ms/step - loss: 0.2573 - accuracy: 0.9125

53/53 [==============================] - 1s 25ms/step - loss: 0.2573 - accuracy: 0.9125 - val_loss: 0.7342 - val_accuracy: 0.7461
Epoch 5/50

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53/53 [==============================] - 1s 22ms/step - loss: 0.1780 - accuracy: 0.9433

53/53 [==============================] - 1s 27ms/step - loss: 0.1780 - accuracy: 0.9433 - val_loss: 0.8425 - val_accuracy: 0.7428
Epoch 6/50

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53/53 [==============================] - 1s 25ms/step - loss: 0.1178 - accuracy: 0.9661 - val_loss: 0.9517 - val_accuracy: 0.7411
Epoch 7/50

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53/53 [==============================] - 1s 26ms/step - loss: 0.0723 - accuracy: 0.9820 - val_loss: 1.0882 - val_accuracy: 0.7378
Epoch 8/50

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53/53 [==============================] - 1s 26ms/step - loss: 0.0382 - accuracy: 0.9926 - val_loss: 1.2167 - val_accuracy: 0.7343
Epoch 9/50

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53/53 [==============================] - 1s 26ms/step - loss: 0.0208 - accuracy: 0.9966 - val_loss: 1.3299 - val_accuracy: 0.7306
Epoch 10/50

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53/53 [==============================] - 1s 21ms/step - loss: 0.0121 - accuracy: 0.9983

53/53 [==============================] - 1s 25ms/step - loss: 0.0121 - accuracy: 0.9983 - val_loss: 1.4061 - val_accuracy: 0.7328
Epoch 11/50

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53/53 [==============================] - 1s 19ms/step - loss: 0.0085 - accuracy: 0.9987

53/53 [==============================] - 1s 24ms/step - loss: 0.0085 - accuracy: 0.9987 - val_loss: 1.5035 - val_accuracy: 0.7341
Epoch 12/50

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53/53 [==============================] - 1s 20ms/step - loss: 0.0060 - accuracy: 0.9992

53/53 [==============================] - 1s 24ms/step - loss: 0.0060 - accuracy: 0.9992 - val_loss: 1.5390 - val_accuracy: 0.7322
Epoch 13/50

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53/53 [==============================] - 1s 21ms/step - loss: 0.0051 - accuracy: 0.9992

53/53 [==============================] - 1s 26ms/step - loss: 0.0051 - accuracy: 0.9992 - val_loss: 1.5951 - val_accuracy: 0.7312
Epoch 14/50

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53/53 [==============================] - 1s 24ms/step - loss: 0.0044 - accuracy: 0.9992 - val_loss: 1.6279 - val_accuracy: 0.7296
Epoch 15/50

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53/53 [==============================] - 1s 19ms/step - loss: 0.0034 - accuracy: 0.9994

53/53 [==============================] - 1s 24ms/step - loss: 0.0034 - accuracy: 0.9994 - val_loss: 1.6759 - val_accuracy: 0.7297
Epoch 16/50

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53/53 [==============================] - 1s 22ms/step - loss: 0.0031 - accuracy: 0.9993

53/53 [==============================] - 1s 26ms/step - loss: 0.0031 - accuracy: 0.9993 - val_loss: 1.7068 - val_accuracy: 0.7265
Epoch 17/50

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53/53 [==============================] - 1s 27ms/step - loss: 0.0033 - accuracy: 0.9995 - val_loss: 1.7301 - val_accuracy: 0.7322
Epoch 18/50

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53/53 [==============================] - 1s 19ms/step - loss: 0.0024 - accuracy: 0.9994

53/53 [==============================] - 1s 23ms/step - loss: 0.0024 - accuracy: 0.9994 - val_loss: 1.7621 - val_accuracy: 0.7302
Epoch 19/50

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53/53 [==============================] - 1s 19ms/step - loss: 0.0023 - accuracy: 0.9995

53/53 [==============================] - 1s 23ms/step - loss: 0.0023 - accuracy: 0.9995 - val_loss: 1.7912 - val_accuracy: 0.7308
Epoch 20/50

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53/53 [==============================] - 1s 20ms/step - loss: 0.0023 - accuracy: 0.9994

53/53 [==============================] - 1s 24ms/step - loss: 0.0023 - accuracy: 0.9994 - val_loss: 1.8214 - val_accuracy: 0.7284
Epoch 21/50

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53/53 [==============================] - 1s 21ms/step - loss: 0.0021 - accuracy: 0.9995

53/53 [==============================] - 1s 26ms/step - loss: 0.0021 - accuracy: 0.9995 - val_loss: 1.8362 - val_accuracy: 0.7303
Epoch 22/50

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53/53 [==============================] - 1s 19ms/step - loss: 0.0020 - accuracy: 0.9995

53/53 [==============================] - 1s 24ms/step - loss: 0.0020 - accuracy: 0.9995 - val_loss: 1.8582 - val_accuracy: 0.7308
Epoch 23/50

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53/53 [==============================] - 1s 20ms/step - loss: 0.0019 - accuracy: 0.9994

53/53 [==============================] - 1s 25ms/step - loss: 0.0019 - accuracy: 0.9994 - val_loss: 1.8990 - val_accuracy: 0.7256
Epoch 24/50

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53/53 [==============================] - 1s 22ms/step - loss: 0.0017 - accuracy: 0.9995

53/53 [==============================] - 1s 27ms/step - loss: 0.0017 - accuracy: 0.9995 - val_loss: 1.9010 - val_accuracy: 0.7287
Epoch 25/50

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53/53 [==============================] - 1s 22ms/step - loss: 0.0017 - accuracy: 0.9995

53/53 [==============================] - 1s 26ms/step - loss: 0.0017 - accuracy: 0.9995 - val_loss: 1.9473 - val_accuracy: 0.7275
Epoch 26/50

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53/53 [==============================] - 1s 22ms/step - loss: 0.0019 - accuracy: 0.9996

53/53 [==============================] - 1s 27ms/step - loss: 0.0019 - accuracy: 0.9996 - val_loss: 1.9535 - val_accuracy: 0.7255
Epoch 27/50

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53/53 [==============================] - 1s 21ms/step - loss: 0.0020 - accuracy: 0.9995

53/53 [==============================] - 1s 26ms/step - loss: 0.0020 - accuracy: 0.9995 - val_loss: 1.9591 - val_accuracy: 0.7285
Epoch 28/50

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53/53 [==============================] - 1s 21ms/step - loss: 0.0036 - accuracy: 0.9991

53/53 [==============================] - 1s 25ms/step - loss: 0.0036 - accuracy: 0.9991 - val_loss: 1.9705 - val_accuracy: 0.7319
Epoch 29/50

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53/53 [==============================] - 1s 20ms/step - loss: 0.0126 - accuracy: 0.9965

53/53 [==============================] - 1s 25ms/step - loss: 0.0126 - accuracy: 0.9965 - val_loss: 1.8683 - val_accuracy: 0.7278
Epoch 30/50

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53/53 [==============================] - 1s 19ms/step - loss: 0.0637 - accuracy: 0.9803

53/53 [==============================] - 1s 24ms/step - loss: 0.0637 - accuracy: 0.9803 - val_loss: 1.4426 - val_accuracy: 0.7129
Epoch 31/50

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53/53 [==============================] - 1s 21ms/step - loss: 0.0718 - accuracy: 0.9766

53/53 [==============================] - 1s 26ms/step - loss: 0.0718 - accuracy: 0.9766 - val_loss: 1.5597 - val_accuracy: 0.7174
Epoch 32/50

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53/53 [==============================] - 1s 26ms/step - loss: 0.0346 - accuracy: 0.9891 - val_loss: 1.5598 - val_accuracy: 0.7218
Epoch 33/50

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53/53 [==============================] - 1s 25ms/step - loss: 0.0132 - accuracy: 0.9973 - val_loss: 1.7064 - val_accuracy: 0.7308
Epoch 34/50

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53/53 [==============================] - 1s 21ms/step - loss: 0.0051 - accuracy: 0.9991

53/53 [==============================] - 1s 25ms/step - loss: 0.0051 - accuracy: 0.9991 - val_loss: 1.7907 - val_accuracy: 0.7259
Epoch 35/50

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53/53 [==============================] - 1s 25ms/step - loss: 0.0026 - accuracy: 0.9994 - val_loss: 1.8368 - val_accuracy: 0.7288
Epoch 36/50

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53/53 [==============================] - 1s 24ms/step - loss: 0.0018 - accuracy: 0.9995 - val_loss: 1.8834 - val_accuracy: 0.7300
Epoch 37/50

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53/53 [==============================] - 1s 25ms/step - loss: 0.0013 - accuracy: 0.9996 - val_loss: 1.9202 - val_accuracy: 0.7296
Epoch 38/50

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53/53 [==============================] - 1s 24ms/step - loss: 0.0011 - accuracy: 0.9997 - val_loss: 1.9539 - val_accuracy: 0.7284
Epoch 39/50

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53/53 [==============================] - 1s 24ms/step - loss: 0.0013 - accuracy: 0.9996 - val_loss: 1.9765 - val_accuracy: 0.7308
Epoch 40/50

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53/53 [==============================] - 1s 24ms/step - loss: 0.0012 - accuracy: 0.9995 - val_loss: 2.0124 - val_accuracy: 0.7278
Epoch 41/50

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53/53 [==============================] - 1s 24ms/step - loss: 0.0011 - accuracy: 0.9996 - val_loss: 2.0422 - val_accuracy: 0.7293
Epoch 42/50

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53/53 [==============================] - 1s 24ms/step - loss: 0.0011 - accuracy: 0.9996 - val_loss: 2.0449 - val_accuracy: 0.7299
Epoch 43/50

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53/53 [==============================] - 1s 20ms/step - loss: 9.7719e-04 - accuracy: 0.9997

53/53 [==============================] - 1s 24ms/step - loss: 9.7719e-04 - accuracy: 0.9997 - val_loss: 2.0636 - val_accuracy: 0.7297
Epoch 44/50

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53/53 [==============================] - 1s 24ms/step - loss: 0.0011 - accuracy: 0.9995 - val_loss: 2.0862 - val_accuracy: 0.7297
Epoch 45/50

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53/53 [==============================] - 1s 25ms/step - loss: 0.0011 - accuracy: 0.9996 - val_loss: 2.0993 - val_accuracy: 0.7293
Epoch 46/50

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53/53 [==============================] - 1s 25ms/step - loss: 9.1871e-04 - accuracy: 0.9997 - val_loss: 2.1189 - val_accuracy: 0.7294
Epoch 47/50

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53/53 [==============================] - 1s 24ms/step - loss: 9.9282e-04 - accuracy: 0.9997 - val_loss: 2.1077 - val_accuracy: 0.7325
Epoch 48/50

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53/53 [==============================] - 1s 25ms/step - loss: 9.9806e-04 - accuracy: 0.9997 - val_loss: 2.1163 - val_accuracy: 0.7302
Epoch 49/50

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53/53 [==============================] - 1s 24ms/step - loss: 0.0012 - accuracy: 0.9996 - val_loss: 2.1402 - val_accuracy: 0.7281
Epoch 50/50

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53/53 [==============================] - 1s 24ms/step - loss: 0.0011 - accuracy: 0.9997 - val_loss: 2.1622 - val_accuracy: 0.7279

Run completed: runs/2023-03-31T02-04-15Z

Training run 3/9 (flags = list(392, 0.001, 200, 30, "sigmoid")) 
Using run directory runs/2023-03-31T02-05-23Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 5000) %>%
+   layer_dense(units = FLAGS$nodes, activatio .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('accuracy .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   covid_train_dtm,covid_train$Sentiment, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(covid_valid_d .... [TRUNCATED] 
Epoch 1/30

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132/132 [==============================] - 3s 17ms/step - loss: 0.7933 - accuracy: 0.6476

132/132 [==============================] - 3s 23ms/step - loss: 0.7933 - accuracy: 0.6476 - val_loss: 0.6410 - val_accuracy: 0.7361
Epoch 2/30

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132/132 [==============================] - 3s 22ms/step - loss: 0.4878 - accuracy: 0.8183 - val_loss: 0.5994 - val_accuracy: 0.7656
Epoch 3/30

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132/132 [==============================] - 3s 19ms/step - loss: 0.4001 - accuracy: 0.8569

132/132 [==============================] - 3s 22ms/step - loss: 0.4001 - accuracy: 0.8569 - val_loss: 0.6195 - val_accuracy: 0.7607
Epoch 4/30

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132/132 [==============================] - 3s 23ms/step - loss: 0.3375 - accuracy: 0.8817 - val_loss: 0.6648 - val_accuracy: 0.7586
Epoch 5/30

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132/132 [==============================] - 3s 23ms/step - loss: 0.2724 - accuracy: 0.9069 - val_loss: 0.7316 - val_accuracy: 0.7537
Epoch 6/30

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132/132 [==============================] - 3s 22ms/step - loss: 0.2155 - accuracy: 0.9301 - val_loss: 0.8387 - val_accuracy: 0.7466
Epoch 7/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.1612 - accuracy: 0.9514

132/132 [==============================] - 3s 24ms/step - loss: 0.1612 - accuracy: 0.9514 - val_loss: 0.9494 - val_accuracy: 0.7396
Epoch 8/30

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132/132 [==============================] - 3s 22ms/step - loss: 0.1068 - accuracy: 0.9708

132/132 [==============================] - 3s 25ms/step - loss: 0.1068 - accuracy: 0.9708 - val_loss: 1.0767 - val_accuracy: 0.7413
Epoch 9/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.0704 - accuracy: 0.9825

132/132 [==============================] - 3s 23ms/step - loss: 0.0704 - accuracy: 0.9825 - val_loss: 1.2328 - val_accuracy: 0.7323
Epoch 10/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.0453 - accuracy: 0.9898 - val_loss: 1.3574 - val_accuracy: 0.7334
Epoch 11/30

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132/132 [==============================] - 2s 18ms/step - loss: 0.0286 - accuracy: 0.9946

132/132 [==============================] - 3s 21ms/step - loss: 0.0286 - accuracy: 0.9946 - val_loss: 1.4863 - val_accuracy: 0.7320
Epoch 12/30

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132/132 [==============================] - 3s 19ms/step - loss: 0.0183 - accuracy: 0.9967

132/132 [==============================] - 3s 22ms/step - loss: 0.0183 - accuracy: 0.9967 - val_loss: 1.6066 - val_accuracy: 0.7293
Epoch 13/30

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132/132 [==============================] - 3s 20ms/step - loss: 0.0111 - accuracy: 0.9981

132/132 [==============================] - 3s 22ms/step - loss: 0.0111 - accuracy: 0.9981 - val_loss: 1.7220 - val_accuracy: 0.7309
Epoch 14/30

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132/132 [==============================] - 3s 22ms/step - loss: 0.0084 - accuracy: 0.9987 - val_loss: 1.7945 - val_accuracy: 0.7305
Epoch 15/30

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132/132 [==============================] - 3s 22ms/step - loss: 0.0068 - accuracy: 0.9991 - val_loss: 1.8787 - val_accuracy: 0.7273
Epoch 16/30

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132/132 [==============================] - 3s 23ms/step - loss: 0.0061 - accuracy: 0.9991 - val_loss: 1.9095 - val_accuracy: 0.7290
Epoch 17/30

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132/132 [==============================] - 3s 23ms/step - loss: 0.0056 - accuracy: 0.9992 - val_loss: 1.9628 - val_accuracy: 0.7316
Epoch 18/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.0065 - accuracy: 0.9989 - val_loss: 1.9669 - val_accuracy: 0.7303
Epoch 19/30

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132/132 [==============================] - 3s 20ms/step - loss: 0.0068 - accuracy: 0.9985

132/132 [==============================] - 3s 23ms/step - loss: 0.0068 - accuracy: 0.9985 - val_loss: 2.0367 - val_accuracy: 0.7234
Epoch 20/30

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132/132 [==============================] - 3s 22ms/step - loss: 0.0132 - accuracy: 0.9966 - val_loss: 1.9596 - val_accuracy: 0.7300
Epoch 21/30

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132/132 [==============================] - 3s 22ms/step - loss: 0.0199 - accuracy: 0.9945 - val_loss: 1.9453 - val_accuracy: 0.7285
Epoch 22/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.0283 - accuracy: 0.9924 - val_loss: 1.8949 - val_accuracy: 0.7252
Epoch 23/30

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132/132 [==============================] - 3s 20ms/step - loss: 0.0254 - accuracy: 0.9929 - val_loss: 1.9207 - val_accuracy: 0.7325
Epoch 24/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.0109 - accuracy: 0.9975 - val_loss: 2.0111 - val_accuracy: 0.7264
Epoch 25/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.0055 - accuracy: 0.9990 - val_loss: 2.0542 - val_accuracy: 0.7332
Epoch 26/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.0031 - accuracy: 0.9994 - val_loss: 2.1478 - val_accuracy: 0.7267
Epoch 27/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.0028 - accuracy: 0.9995 - val_loss: 2.2096 - val_accuracy: 0.7291
Epoch 28/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.0023 - accuracy: 0.9994 - val_loss: 2.2372 - val_accuracy: 0.7294
Epoch 29/30

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132/132 [==============================] - 3s 21ms/step - loss: 0.0018 - accuracy: 0.9996 - val_loss: 2.2692 - val_accuracy: 0.7303
Epoch 30/30

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132/132 [==============================] - 3s 20ms/step - loss: 0.0017 - accuracy: 0.9995 - val_loss: 2.3104 - val_accuracy: 0.7300

Run completed: runs/2023-03-31T02-05-23Z

Training run 4/9 (flags = list(128, 0.01, 100, 30, "tanh")) 
Using run directory runs/2023-03-31T02-06-50Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 5000) %>%
+   layer_dense(units = FLAGS$nodes, activatio .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('accuracy .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   covid_train_dtm,covid_train$Sentiment, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(covid_valid_d .... [TRUNCATED] 
Epoch 1/30

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264/264 [==============================] - 2s 5ms/step - loss: 0.7272 - accuracy: 0.6902

264/264 [==============================] - 2s 8ms/step - loss: 0.7272 - accuracy: 0.6902 - val_loss: 0.5995 - val_accuracy: 0.7609
Epoch 2/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.4329 - accuracy: 0.8391

264/264 [==============================] - 2s 6ms/step - loss: 0.4329 - accuracy: 0.8391 - val_loss: 0.6060 - val_accuracy: 0.7663
Epoch 3/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.3004 - accuracy: 0.8919

264/264 [==============================] - 1s 6ms/step - loss: 0.3004 - accuracy: 0.8919 - val_loss: 0.6778 - val_accuracy: 0.7558
Epoch 4/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.1851 - accuracy: 0.9367

264/264 [==============================] - 2s 6ms/step - loss: 0.1851 - accuracy: 0.9367 - val_loss: 0.8222 - val_accuracy: 0.7531
Epoch 5/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.0961 - accuracy: 0.9699

264/264 [==============================] - 2s 6ms/step - loss: 0.0961 - accuracy: 0.9699 - val_loss: 0.9752 - val_accuracy: 0.7449
Epoch 6/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.0409 - accuracy: 0.9904

264/264 [==============================] - 1s 6ms/step - loss: 0.0409 - accuracy: 0.9904 - val_loss: 1.1762 - val_accuracy: 0.7475
Epoch 7/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.0185 - accuracy: 0.9960

264/264 [==============================] - 2s 6ms/step - loss: 0.0185 - accuracy: 0.9960 - val_loss: 1.3335 - val_accuracy: 0.7470
Epoch 8/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.0118 - accuracy: 0.9975

264/264 [==============================] - 1s 6ms/step - loss: 0.0118 - accuracy: 0.9975 - val_loss: 1.4131 - val_accuracy: 0.7469
Epoch 9/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.0071 - accuracy: 0.9986

264/264 [==============================] - 2s 6ms/step - loss: 0.0071 - accuracy: 0.9986 - val_loss: 1.5515 - val_accuracy: 0.7493
Epoch 10/30

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264/264 [==============================] - 2s 6ms/step - loss: 0.0057 - accuracy: 0.9987 - val_loss: 1.6025 - val_accuracy: 0.7451
Epoch 11/30

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264/264 [==============================] - 2s 6ms/step - loss: 0.0070 - accuracy: 0.9985 - val_loss: 1.6470 - val_accuracy: 0.7443
Epoch 12/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.0164 - accuracy: 0.9956

264/264 [==============================] - 2s 6ms/step - loss: 0.0164 - accuracy: 0.9956 - val_loss: 1.6698 - val_accuracy: 0.7308
Epoch 13/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.0394 - accuracy: 0.9863

264/264 [==============================] - 2s 6ms/step - loss: 0.0394 - accuracy: 0.9863 - val_loss: 1.6868 - val_accuracy: 0.7258
Epoch 14/30

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264/264 [==============================] - 1s 6ms/step - loss: 0.0297 - accuracy: 0.9907 - val_loss: 1.6854 - val_accuracy: 0.7360
Epoch 15/30

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264/264 [==============================] - 2s 6ms/step - loss: 0.0155 - accuracy: 0.9957 - val_loss: 1.6691 - val_accuracy: 0.7316
Epoch 16/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.0064 - accuracy: 0.9982

264/264 [==============================] - 1s 6ms/step - loss: 0.0064 - accuracy: 0.9982 - val_loss: 1.7921 - val_accuracy: 0.7357
Epoch 17/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.0051 - accuracy: 0.9986

264/264 [==============================] - 2s 6ms/step - loss: 0.0051 - accuracy: 0.9986 - val_loss: 1.8572 - val_accuracy: 0.7376
Epoch 18/30

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264/264 [==============================] - 2s 6ms/step - loss: 0.0023 - accuracy: 0.9993 - val_loss: 1.9678 - val_accuracy: 0.7349
Epoch 19/30

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264/264 [==============================] - 1s 6ms/step - loss: 0.0024 - accuracy: 0.9994 - val_loss: 1.9472 - val_accuracy: 0.7382
Epoch 20/30

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264/264 [==============================] - 1s 6ms/step - loss: 0.0035 - accuracy: 0.9991 - val_loss: 2.0246 - val_accuracy: 0.7398
Epoch 21/30

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264/264 [==============================] - 2s 6ms/step - loss: 0.0052 - accuracy: 0.9986 - val_loss: 2.0082 - val_accuracy: 0.7414
Epoch 22/30

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264/264 [==============================] - 1s 5ms/step - loss: 0.0082 - accuracy: 0.9980

264/264 [==============================] - 1s 6ms/step - loss: 0.0082 - accuracy: 0.9980 - val_loss: 1.9595 - val_accuracy: 0.7378
Epoch 23/30

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264/264 [==============================] - 2s 6ms/step - loss: 0.0051 - accuracy: 0.9981 - val_loss: 2.0244 - val_accuracy: 0.7316
Epoch 24/30

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264/264 [==============================] - 1s 6ms/step - loss: 0.0136 - accuracy: 0.9956 - val_loss: 1.9438 - val_accuracy: 0.7312
Epoch 25/30

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264/264 [==============================] - 2s 6ms/step - loss: 0.0131 - accuracy: 0.9954 - val_loss: 2.0689 - val_accuracy: 0.7319
Epoch 26/30

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264/264 [==============================] - 2s 6ms/step - loss: 0.0182 - accuracy: 0.9948 - val_loss: 2.0569 - val_accuracy: 0.7367
Epoch 27/30

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264/264 [==============================] - 1s 6ms/step - loss: 0.0082 - accuracy: 0.9979 - val_loss: 1.9924 - val_accuracy: 0.7361
Epoch 28/30

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264/264 [==============================] - 1s 6ms/step - loss: 0.0030 - accuracy: 0.9992 - val_loss: 2.1294 - val_accuracy: 0.7350
Epoch 29/30

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264/264 [==============================] - 2s 6ms/step - loss: 0.0019 - accuracy: 0.9994 - val_loss: 2.0959 - val_accuracy: 0.7326
Epoch 30/30

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264/264 [==============================] - 2s 6ms/step - loss: 0.0019 - accuracy: 0.9994 - val_loss: 2.1042 - val_accuracy: 0.7344

Run completed: runs/2023-03-31T02-06-50Z

Training run 5/9 (flags = list(128, 0.01, 500, 50, "tanh")) 
Using run directory runs/2023-03-31T02-07-36Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 5000) %>%
+   layer_dense(units = FLAGS$nodes, activatio .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('accuracy .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   covid_train_dtm,covid_train$Sentiment, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(covid_valid_d .... [TRUNCATED] 
Epoch 1/50

 1/53 [..............................] - ETA: 17s - loss: 1.2416 - accuracy: 0.3600
 8/53 [===>..........................] - ETA: 0s - loss: 1.0631 - accuracy: 0.4330 
15/53 [=======>......................] - ETA: 0s - loss: 1.0026 - accuracy: 0.4879
22/53 [===========>..................] - ETA: 0s - loss: 0.9599 - accuracy: 0.5293
29/53 [===============>..............] - ETA: 0s - loss: 0.9214 - accuracy: 0.5586
36/53 [===================>..........] - ETA: 0s - loss: 0.8870 - accuracy: 0.5824
43/53 [=======================>......] - ETA: 0s - loss: 0.8575 - accuracy: 0.6028
50/53 [===========================>..] - ETA: 0s - loss: 0.8277 - accuracy: 0.6216
53/53 [==============================] - 1s 8ms/step - loss: 0.8201 - accuracy: 0.6265

53/53 [==============================] - 1s 21ms/step - loss: 0.8201 - accuracy: 0.6265 - val_loss: 0.6504 - val_accuracy: 0.7267
Epoch 2/50

 1/53 [..............................] - ETA: 0s - loss: 0.4888 - accuracy: 0.8240
 7/53 [==>...........................] - ETA: 0s - loss: 0.4683 - accuracy: 0.8266
13/53 [======>.......................] - ETA: 0s - loss: 0.4552 - accuracy: 0.8372
20/53 [==========>...................] - ETA: 0s - loss: 0.4568 - accuracy: 0.8346
26/53 [=============>................] - ETA: 0s - loss: 0.4604 - accuracy: 0.8318
33/53 [=================>............] - ETA: 0s - loss: 0.4626 - accuracy: 0.8322
40/53 [=====================>........] - ETA: 0s - loss: 0.4618 - accuracy: 0.8308
47/53 [=========================>....] - ETA: 0s - loss: 0.4645 - accuracy: 0.8280
53/53 [==============================] - 0s 8ms/step - loss: 0.4681 - accuracy: 0.8260

53/53 [==============================] - 1s 12ms/step - loss: 0.4681 - accuracy: 0.8260 - val_loss: 0.6184 - val_accuracy: 0.7517
Epoch 3/50

 1/53 [..............................] - ETA: 0s - loss: 0.3683 - accuracy: 0.8840
 8/53 [===>..........................] - ETA: 0s - loss: 0.3120 - accuracy: 0.9028
15/53 [=======>......................] - ETA: 0s - loss: 0.3080 - accuracy: 0.9005
22/53 [===========>..................] - ETA: 0s - loss: 0.3141 - accuracy: 0.8956
29/53 [===============>..............] - ETA: 0s - loss: 0.3211 - accuracy: 0.8921
36/53 [===================>..........] - ETA: 0s - loss: 0.3289 - accuracy: 0.8873
43/53 [=======================>......] - ETA: 0s - loss: 0.3369 - accuracy: 0.8833
50/53 [===========================>..] - ETA: 0s - loss: 0.3446 - accuracy: 0.8806
53/53 [==============================] - 0s 8ms/step - loss: 0.3483 - accuracy: 0.8784

53/53 [==============================] - 1s 12ms/step - loss: 0.3483 - accuracy: 0.8784 - val_loss: 0.6472 - val_accuracy: 0.7540
Epoch 4/50

 1/53 [..............................] - ETA: 0s - loss: 0.2182 - accuracy: 0.9500
 8/53 [===>..........................] - ETA: 0s - loss: 0.2435 - accuracy: 0.9293
14/53 [======>.......................] - ETA: 0s - loss: 0.2385 - accuracy: 0.9313
21/53 [==========>...................] - ETA: 0s - loss: 0.2401 - accuracy: 0.9270
28/53 [==============>...............] - ETA: 0s - loss: 0.2476 - accuracy: 0.9221
35/53 [==================>...........] - ETA: 0s - loss: 0.2521 - accuracy: 0.9191
42/53 [======================>.......] - ETA: 0s - loss: 0.2589 - accuracy: 0.9157
49/53 [==========================>...] - ETA: 0s - loss: 0.2623 - accuracy: 0.9138
53/53 [==============================] - 0s 8ms/step - loss: 0.2656 - accuracy: 0.9120

53/53 [==============================] - 1s 12ms/step - loss: 0.2656 - accuracy: 0.9120 - val_loss: 0.7218 - val_accuracy: 0.7490
Epoch 5/50

 1/53 [..............................] - ETA: 0s - loss: 0.1762 - accuracy: 0.9460
 8/53 [===>..........................] - ETA: 0s - loss: 0.1713 - accuracy: 0.9553
15/53 [=======>......................] - ETA: 0s - loss: 0.1738 - accuracy: 0.9516
22/53 [===========>..................] - ETA: 0s - loss: 0.1807 - accuracy: 0.9494
29/53 [===============>..............] - ETA: 0s - loss: 0.1815 - accuracy: 0.9475
36/53 [===================>..........] - ETA: 0s - loss: 0.1868 - accuracy: 0.9445
43/53 [=======================>......] - ETA: 0s - loss: 0.1907 - accuracy: 0.9429
50/53 [===========================>..] - ETA: 0s - loss: 0.1950 - accuracy: 0.9403
53/53 [==============================] - 0s 8ms/step - loss: 0.1971 - accuracy: 0.9389

53/53 [==============================] - 1s 12ms/step - loss: 0.1971 - accuracy: 0.9389 - val_loss: 0.8062 - val_accuracy: 0.7466
Epoch 6/50

 1/53 [..............................] - ETA: 0s - loss: 0.1156 - accuracy: 0.9680
 8/53 [===>..........................] - ETA: 0s - loss: 0.1152 - accuracy: 0.9743
15/53 [=======>......................] - ETA: 0s - loss: 0.1222 - accuracy: 0.9688
22/53 [===========>..................] - ETA: 0s - loss: 0.1211 - accuracy: 0.9689
29/53 [===============>..............] - ETA: 0s - loss: 0.1245 - accuracy: 0.9668
35/53 [==================>...........] - ETA: 0s - loss: 0.1264 - accuracy: 0.9659
41/53 [======================>.......] - ETA: 0s - loss: 0.1300 - accuracy: 0.9645
47/53 [=========================>....] - ETA: 0s - loss: 0.1318 - accuracy: 0.9640
53/53 [==============================] - 0s 8ms/step - loss: 0.1317 - accuracy: 0.9637

53/53 [==============================] - 1s 12ms/step - loss: 0.1317 - accuracy: 0.9637 - val_loss: 0.9107 - val_accuracy: 0.7373
Epoch 7/50

 1/53 [..............................] - ETA: 0s - loss: 0.0629 - accuracy: 0.9920
 8/53 [===>..........................] - ETA: 0s - loss: 0.0726 - accuracy: 0.9862
15/53 [=======>......................] - ETA: 0s - loss: 0.0732 - accuracy: 0.9861
22/53 [===========>..................] - ETA: 0s - loss: 0.0766 - accuracy: 0.9835
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43/53 [=======================>......] - ETA: 0s - loss: 0.0828 - accuracy: 0.9801
50/53 [===========================>..] - ETA: 0s - loss: 0.0855 - accuracy: 0.9787
53/53 [==============================] - 0s 8ms/step - loss: 0.0862 - accuracy: 0.9782

53/53 [==============================] - 1s 12ms/step - loss: 0.0862 - accuracy: 0.9782 - val_loss: 1.0545 - val_accuracy: 0.7358
Epoch 8/50

 1/53 [..............................] - ETA: 0s - loss: 0.0425 - accuracy: 0.9940
 7/53 [==>...........................] - ETA: 0s - loss: 0.0439 - accuracy: 0.9923
13/53 [======>.......................] - ETA: 0s - loss: 0.0495 - accuracy: 0.9905
20/53 [==========>...................] - ETA: 0s - loss: 0.0498 - accuracy: 0.9905
27/53 [==============>...............] - ETA: 0s - loss: 0.0482 - accuracy: 0.9912
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40/53 [=====================>........] - ETA: 0s - loss: 0.0497 - accuracy: 0.9902
47/53 [=========================>....] - ETA: 0s - loss: 0.0519 - accuracy: 0.9894
53/53 [==============================] - 0s 8ms/step - loss: 0.0534 - accuracy: 0.9890

53/53 [==============================] - 1s 12ms/step - loss: 0.0534 - accuracy: 0.9890 - val_loss: 1.1499 - val_accuracy: 0.7347
Epoch 9/50

 1/53 [..............................] - ETA: 0s - loss: 0.0377 - accuracy: 0.9920
 8/53 [===>..........................] - ETA: 0s - loss: 0.0288 - accuracy: 0.9955
15/53 [=======>......................] - ETA: 0s - loss: 0.0290 - accuracy: 0.9957
22/53 [===========>..................] - ETA: 0s - loss: 0.0303 - accuracy: 0.9949
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50/53 [===========================>..] - ETA: 0s - loss: 0.0299 - accuracy: 0.9950
53/53 [==============================] - 0s 8ms/step - loss: 0.0302 - accuracy: 0.9949

53/53 [==============================] - 1s 12ms/step - loss: 0.0302 - accuracy: 0.9949 - val_loss: 1.2471 - val_accuracy: 0.7372
Epoch 10/50

 1/53 [..............................] - ETA: 0s - loss: 0.0210 - accuracy: 0.9960
 8/53 [===>..........................] - ETA: 0s - loss: 0.0146 - accuracy: 0.9980
15/53 [=======>......................] - ETA: 0s - loss: 0.0158 - accuracy: 0.9976
22/53 [===========>..................] - ETA: 0s - loss: 0.0162 - accuracy: 0.9976
29/53 [===============>..............] - ETA: 0s - loss: 0.0162 - accuracy: 0.9978
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42/53 [======================>.......] - ETA: 0s - loss: 0.0165 - accuracy: 0.9975
49/53 [==========================>...] - ETA: 0s - loss: 0.0166 - accuracy: 0.9974
53/53 [==============================] - 0s 8ms/step - loss: 0.0167 - accuracy: 0.9974

53/53 [==============================] - 1s 12ms/step - loss: 0.0167 - accuracy: 0.9974 - val_loss: 1.3428 - val_accuracy: 0.7332
Epoch 11/50

 1/53 [..............................] - ETA: 0s - loss: 0.0073 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 0.0088 - accuracy: 0.9995
15/53 [=======>......................] - ETA: 0s - loss: 0.0093 - accuracy: 0.9989
22/53 [===========>..................] - ETA: 0s - loss: 0.0103 - accuracy: 0.9987
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49/53 [==========================>...] - ETA: 0s - loss: 0.0100 - accuracy: 0.9987
53/53 [==============================] - 0s 8ms/step - loss: 0.0103 - accuracy: 0.9986

53/53 [==============================] - 1s 12ms/step - loss: 0.0103 - accuracy: 0.9986 - val_loss: 1.4188 - val_accuracy: 0.7331
Epoch 12/50

 1/53 [..............................] - ETA: 0s - loss: 0.0042 - accuracy: 1.0000
 7/53 [==>...........................] - ETA: 0s - loss: 0.0064 - accuracy: 0.9994
13/53 [======>.......................] - ETA: 0s - loss: 0.0070 - accuracy: 0.9994
20/53 [==========>...................] - ETA: 0s - loss: 0.0064 - accuracy: 0.9994
27/53 [==============>...............] - ETA: 0s - loss: 0.0077 - accuracy: 0.9990
34/53 [==================>...........] - ETA: 0s - loss: 0.0077 - accuracy: 0.9991
41/53 [======================>.......] - ETA: 0s - loss: 0.0078 - accuracy: 0.9990
48/53 [==========================>...] - ETA: 0s - loss: 0.0079 - accuracy: 0.9989
53/53 [==============================] - 0s 8ms/step - loss: 0.0078 - accuracy: 0.9989

53/53 [==============================] - 1s 12ms/step - loss: 0.0078 - accuracy: 0.9989 - val_loss: 1.4852 - val_accuracy: 0.7337
Epoch 13/50

 1/53 [..............................] - ETA: 0s - loss: 0.0046 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 0.0050 - accuracy: 0.9995
15/53 [=======>......................] - ETA: 0s - loss: 0.0051 - accuracy: 0.9995
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43/53 [=======================>......] - ETA: 0s - loss: 0.0060 - accuracy: 0.9992
50/53 [===========================>..] - ETA: 0s - loss: 0.0059 - accuracy: 0.9992
53/53 [==============================] - 0s 8ms/step - loss: 0.0060 - accuracy: 0.9992

53/53 [==============================] - 1s 12ms/step - loss: 0.0060 - accuracy: 0.9992 - val_loss: 1.5423 - val_accuracy: 0.7293
Epoch 14/50

 1/53 [..............................] - ETA: 0s - loss: 0.0025 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 0.0040 - accuracy: 0.9998
15/53 [=======>......................] - ETA: 0s - loss: 0.0042 - accuracy: 0.9996
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43/53 [=======================>......] - ETA: 0s - loss: 0.0037 - accuracy: 0.9997
49/53 [==========================>...] - ETA: 0s - loss: 0.0045 - accuracy: 0.9994
53/53 [==============================] - 0s 8ms/step - loss: 0.0046 - accuracy: 0.9994

53/53 [==============================] - 1s 12ms/step - loss: 0.0046 - accuracy: 0.9994 - val_loss: 1.6039 - val_accuracy: 0.7332
Epoch 15/50

 1/53 [..............................] - ETA: 0s - loss: 0.0034 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 0.0032 - accuracy: 0.9998
15/53 [=======>......................] - ETA: 0s - loss: 0.0039 - accuracy: 0.9995
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50/53 [===========================>..] - ETA: 0s - loss: 0.0040 - accuracy: 0.9994
53/53 [==============================] - 0s 8ms/step - loss: 0.0041 - accuracy: 0.9994

53/53 [==============================] - 1s 12ms/step - loss: 0.0041 - accuracy: 0.9994 - val_loss: 1.6348 - val_accuracy: 0.7288
Epoch 16/50

 1/53 [..............................] - ETA: 0s - loss: 0.0026 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 0.0047 - accuracy: 0.9992
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53/53 [==============================] - 0s 8ms/step - loss: 0.0035 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0035 - accuracy: 0.9995 - val_loss: 1.6716 - val_accuracy: 0.7288
Epoch 17/50

 1/53 [..............................] - ETA: 0s - loss: 0.0063 - accuracy: 0.9980
 7/53 [==>...........................] - ETA: 0s - loss: 0.0039 - accuracy: 0.9991
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53/53 [==============================] - 0s 8ms/step - loss: 0.0029 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0029 - accuracy: 0.9995 - val_loss: 1.6928 - val_accuracy: 0.7311
Epoch 18/50

 1/53 [..............................] - ETA: 0s - loss: 8.7819e-04 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 0.0017 - accuracy: 0.9998    
15/53 [=======>......................] - ETA: 0s - loss: 0.0029 - accuracy: 0.9993
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50/53 [===========================>..] - ETA: 0s - loss: 0.0029 - accuracy: 0.9994
53/53 [==============================] - 0s 8ms/step - loss: 0.0031 - accuracy: 0.9994

53/53 [==============================] - 1s 12ms/step - loss: 0.0031 - accuracy: 0.9994 - val_loss: 1.7367 - val_accuracy: 0.7278
Epoch 19/50

 1/53 [..............................] - ETA: 0s - loss: 0.0054 - accuracy: 0.9980
 8/53 [===>..........................] - ETA: 0s - loss: 0.0031 - accuracy: 0.9992
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49/53 [==========================>...] - ETA: 0s - loss: 0.0029 - accuracy: 0.9994
53/53 [==============================] - 0s 8ms/step - loss: 0.0028 - accuracy: 0.9994

53/53 [==============================] - 1s 12ms/step - loss: 0.0028 - accuracy: 0.9994 - val_loss: 1.7457 - val_accuracy: 0.7300
Epoch 20/50

 1/53 [..............................] - ETA: 0s - loss: 0.0011 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 0.0018 - accuracy: 0.9998
15/53 [=======>......................] - ETA: 0s - loss: 0.0016 - accuracy: 0.9997
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50/53 [===========================>..] - ETA: 0s - loss: 0.0022 - accuracy: 0.9996
53/53 [==============================] - 0s 8ms/step - loss: 0.0023 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0023 - accuracy: 0.9995 - val_loss: 1.7985 - val_accuracy: 0.7273
Epoch 21/50

 1/53 [..............................] - ETA: 0s - loss: 0.0012 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 0.0024 - accuracy: 0.9992
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53/53 [==============================] - 0s 8ms/step - loss: 0.0022 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0022 - accuracy: 0.9995 - val_loss: 1.7988 - val_accuracy: 0.7316
Epoch 22/50

 1/53 [..............................] - ETA: 0s - loss: 7.4121e-04 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 0.0015 - accuracy: 0.9998    
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53/53 [==============================] - 0s 8ms/step - loss: 0.0020 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0020 - accuracy: 0.9995 - val_loss: 1.8369 - val_accuracy: 0.7271
Epoch 23/50

 1/53 [..............................] - ETA: 0s - loss: 0.0012 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 9.1386e-04 - accuracy: 1.0000
15/53 [=======>......................] - ETA: 0s - loss: 0.0022 - accuracy: 0.9995    
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53/53 [==============================] - 0s 8ms/step - loss: 0.0019 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0019 - accuracy: 0.9995 - val_loss: 1.8490 - val_accuracy: 0.7294
Epoch 24/50

 1/53 [..............................] - ETA: 0s - loss: 8.6834e-04 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 0.0016 - accuracy: 0.9998    
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53/53 [==============================] - 0s 8ms/step - loss: 0.0019 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0019 - accuracy: 0.9995 - val_loss: 1.8748 - val_accuracy: 0.7294
Epoch 25/50

 1/53 [..............................] - ETA: 0s - loss: 5.5788e-04 - accuracy: 1.0000
 8/53 [===>..........................] - ETA: 0s - loss: 7.8130e-04 - accuracy: 1.0000
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53/53 [==============================] - 0s 8ms/step - loss: 0.0020 - accuracy: 0.9994

53/53 [==============================] - 1s 12ms/step - loss: 0.0020 - accuracy: 0.9994 - val_loss: 1.8956 - val_accuracy: 0.7282
Epoch 26/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0027 - accuracy: 0.9994

53/53 [==============================] - 1s 12ms/step - loss: 0.0027 - accuracy: 0.9994 - val_loss: 1.9275 - val_accuracy: 0.7278
Epoch 27/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0029 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0029 - accuracy: 0.9995 - val_loss: 1.9201 - val_accuracy: 0.7281
Epoch 28/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0031 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0031 - accuracy: 0.9995 - val_loss: 1.9222 - val_accuracy: 0.7287
Epoch 29/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0026 - accuracy: 0.9993

53/53 [==============================] - 1s 12ms/step - loss: 0.0026 - accuracy: 0.9993 - val_loss: 1.9529 - val_accuracy: 0.7297
Epoch 30/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0051 - accuracy: 0.9986

53/53 [==============================] - 1s 12ms/step - loss: 0.0051 - accuracy: 0.9986 - val_loss: 1.9946 - val_accuracy: 0.7282
Epoch 31/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0382 - accuracy: 0.9871

53/53 [==============================] - 1s 12ms/step - loss: 0.0382 - accuracy: 0.9871 - val_loss: 1.7370 - val_accuracy: 0.7150
Epoch 32/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.1233 - accuracy: 0.9575

53/53 [==============================] - 1s 12ms/step - loss: 0.1233 - accuracy: 0.9575 - val_loss: 1.4402 - val_accuracy: 0.7179
Epoch 33/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0497 - accuracy: 0.9849

53/53 [==============================] - 1s 12ms/step - loss: 0.0497 - accuracy: 0.9849 - val_loss: 1.5076 - val_accuracy: 0.7250
Epoch 34/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0130 - accuracy: 0.9971

53/53 [==============================] - 1s 12ms/step - loss: 0.0130 - accuracy: 0.9971 - val_loss: 1.6378 - val_accuracy: 0.7312
Epoch 35/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0040 - accuracy: 0.9994

53/53 [==============================] - 1s 11ms/step - loss: 0.0040 - accuracy: 0.9994 - val_loss: 1.7053 - val_accuracy: 0.7326
Epoch 36/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0022 - accuracy: 0.9996

53/53 [==============================] - 1s 12ms/step - loss: 0.0022 - accuracy: 0.9996 - val_loss: 1.7600 - val_accuracy: 0.7338
Epoch 37/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0017 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0017 - accuracy: 0.9995 - val_loss: 1.7997 - val_accuracy: 0.7337
Epoch 38/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0015 - accuracy: 0.9995

53/53 [==============================] - 1s 12ms/step - loss: 0.0015 - accuracy: 0.9995 - val_loss: 1.8355 - val_accuracy: 0.7323
Epoch 39/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0014 - accuracy: 0.9997

53/53 [==============================] - 1s 12ms/step - loss: 0.0014 - accuracy: 0.9997 - val_loss: 1.8596 - val_accuracy: 0.7326
Epoch 40/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0013 - accuracy: 0.9996

53/53 [==============================] - 1s 13ms/step - loss: 0.0013 - accuracy: 0.9996 - val_loss: 1.8879 - val_accuracy: 0.7329
Epoch 41/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0013 - accuracy: 0.9996

53/53 [==============================] - 1s 12ms/step - loss: 0.0013 - accuracy: 0.9996 - val_loss: 1.9199 - val_accuracy: 0.7329
Epoch 42/50

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53/53 [==============================] - 1s 10ms/step - loss: 0.0012 - accuracy: 0.9996

53/53 [==============================] - 1s 14ms/step - loss: 0.0012 - accuracy: 0.9996 - val_loss: 1.9335 - val_accuracy: 0.7319
Epoch 43/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0012 - accuracy: 0.9996

53/53 [==============================] - 1s 12ms/step - loss: 0.0012 - accuracy: 0.9996 - val_loss: 1.9435 - val_accuracy: 0.7344
Epoch 44/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0012 - accuracy: 0.9997

53/53 [==============================] - 1s 12ms/step - loss: 0.0012 - accuracy: 0.9997 - val_loss: 1.9639 - val_accuracy: 0.7312
Epoch 45/50

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53/53 [==============================] - 0s 9ms/step - loss: 0.0012 - accuracy: 0.9995

53/53 [==============================] - 1s 13ms/step - loss: 0.0012 - accuracy: 0.9995 - val_loss: 1.9813 - val_accuracy: 0.7314
Epoch 46/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0011 - accuracy: 0.9996

53/53 [==============================] - 1s 12ms/step - loss: 0.0011 - accuracy: 0.9996 - val_loss: 1.9985 - val_accuracy: 0.7343
Epoch 47/50

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53/53 [==============================] - 0s 8ms/step - loss: 0.0011 - accuracy: 0.9997

53/53 [==============================] - 1s 12ms/step - loss: 0.0011 - accuracy: 0.9997 - val_loss: 2.0044 - val_accuracy: 0.7340
Epoch 48/50

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53/53 [==============================] - 0s 9ms/step - loss: 9.3213e-04 - accuracy: 0.9996

53/53 [==============================] - 1s 13ms/step - loss: 9.3213e-04 - accuracy: 0.9996 - val_loss: 2.0201 - val_accuracy: 0.7357
Epoch 49/50

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51/53 [===========================>..] - ETA: 0s - loss: 0.0010 - accuracy: 0.9996
53/53 [==============================] - 0s 9ms/step - loss: 9.9149e-04 - accuracy: 0.9997

53/53 [==============================] - 1s 13ms/step - loss: 9.9149e-04 - accuracy: 0.9997 - val_loss: 2.0473 - val_accuracy: 0.7312
Epoch 50/50

 1/53 [..............................] - ETA: 0s - loss: 2.0288e-04 - accuracy: 1.0000
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20/53 [==========>...................] - ETA: 0s - loss: 4.3707e-04 - accuracy: 0.9999
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48/53 [==========================>...] - ETA: 0s - loss: 6.5618e-04 - accuracy: 0.9998
53/53 [==============================] - 0s 8ms/step - loss: 8.9072e-04 - accuracy: 0.9997

53/53 [==============================] - 1s 12ms/step - loss: 8.9072e-04 - accuracy: 0.9997 - val_loss: 2.0544 - val_accuracy: 0.7338

Run completed: runs/2023-03-31T02-07-36Z

Training run 6/9 (flags = list(64, 1e-04, 1000, 50, "tanh")) 
Using run directory runs/2023-03-31T02-08-09Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 5000) %>%
+   layer_dense(units = FLAGS$nodes, activatio .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('accuracy .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   covid_train_dtm,covid_train$Sentiment, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(covid_valid_d .... [TRUNCATED] 
Epoch 1/50

 1/27 [>.............................] - ETA: 9s - loss: 1.4295 - accuracy: 0.3770
 7/27 [======>.......................] - ETA: 0s - loss: 1.1489 - accuracy: 0.4171
13/27 [=============>................] - ETA: 0s - loss: 1.0727 - accuracy: 0.4634
19/27 [====================>.........] - ETA: 0s - loss: 1.0264 - accuracy: 0.5029
25/27 [==========================>...] - ETA: 0s - loss: 0.9832 - accuracy: 0.5363
27/27 [==============================] - 1s 9ms/step - loss: 0.9746 - accuracy: 0.5424

27/27 [==============================] - 1s 36ms/step - loss: 0.9746 - accuracy: 0.5424 - val_loss: 0.8032 - val_accuracy: 0.6493
Epoch 2/50

 1/27 [>.............................] - ETA: 0s - loss: 0.7184 - accuracy: 0.7070
 6/27 [=====>........................] - ETA: 0s - loss: 0.7047 - accuracy: 0.7213
12/27 [============>.................] - ETA: 0s - loss: 0.6698 - accuracy: 0.7322
18/27 [===================>..........] - ETA: 0s - loss: 0.6470 - accuracy: 0.7420
24/27 [=========================>....] - ETA: 0s - loss: 0.6279 - accuracy: 0.7516
27/27 [==============================] - 0s 9ms/step - loss: 0.6228 - accuracy: 0.7535

27/27 [==============================] - 0s 17ms/step - loss: 0.6228 - accuracy: 0.7535 - val_loss: 0.6442 - val_accuracy: 0.7347
Epoch 3/50

 1/27 [>.............................] - ETA: 0s - loss: 0.4444 - accuracy: 0.8570
 7/27 [======>.......................] - ETA: 0s - loss: 0.4415 - accuracy: 0.8534
14/27 [==============>...............] - ETA: 0s - loss: 0.4369 - accuracy: 0.8491
20/27 [=====================>........] - ETA: 0s - loss: 0.4381 - accuracy: 0.8472
26/27 [===========================>..] - ETA: 0s - loss: 0.4440 - accuracy: 0.8440
27/27 [==============================] - 0s 8ms/step - loss: 0.4431 - accuracy: 0.8445

27/27 [==============================] - 0s 15ms/step - loss: 0.4431 - accuracy: 0.8445 - val_loss: 0.6206 - val_accuracy: 0.7524
Epoch 4/50

 1/27 [>.............................] - ETA: 0s - loss: 0.3284 - accuracy: 0.9010
 7/27 [======>.......................] - ETA: 0s - loss: 0.3364 - accuracy: 0.8959
14/27 [==============>...............] - ETA: 0s - loss: 0.3445 - accuracy: 0.8894
21/27 [======================>.......] - ETA: 0s - loss: 0.3526 - accuracy: 0.8825
27/27 [==============================] - 0s 8ms/step - loss: 0.3563 - accuracy: 0.8801

27/27 [==============================] - 0s 15ms/step - loss: 0.3563 - accuracy: 0.8801 - val_loss: 0.6409 - val_accuracy: 0.7536
Epoch 5/50

 1/27 [>.............................] - ETA: 0s - loss: 0.2716 - accuracy: 0.9210
 7/27 [======>.......................] - ETA: 0s - loss: 0.2870 - accuracy: 0.9139
13/27 [=============>................] - ETA: 0s - loss: 0.2929 - accuracy: 0.9101
19/27 [====================>.........] - ETA: 0s - loss: 0.2941 - accuracy: 0.9066
26/27 [===========================>..] - ETA: 0s - loss: 0.3002 - accuracy: 0.9022
27/27 [==============================] - 0s 9ms/step - loss: 0.3004 - accuracy: 0.9019

27/27 [==============================] - 0s 16ms/step - loss: 0.3004 - accuracy: 0.9019 - val_loss: 0.6714 - val_accuracy: 0.7555
Epoch 6/50

 1/27 [>.............................] - ETA: 0s - loss: 0.2341 - accuracy: 0.9330
 7/27 [======>.......................] - ETA: 0s - loss: 0.2388 - accuracy: 0.9316
13/27 [=============>................] - ETA: 0s - loss: 0.2437 - accuracy: 0.9295
19/27 [====================>.........] - ETA: 0s - loss: 0.2496 - accuracy: 0.9253
25/27 [==========================>...] - ETA: 0s - loss: 0.2553 - accuracy: 0.9207
27/27 [==============================] - 0s 9ms/step - loss: 0.2574 - accuracy: 0.9197

27/27 [==============================] - 0s 16ms/step - loss: 0.2574 - accuracy: 0.9197 - val_loss: 0.7111 - val_accuracy: 0.7478
Epoch 7/50

 1/27 [>.............................] - ETA: 0s - loss: 0.1978 - accuracy: 0.9450
 7/27 [======>.......................] - ETA: 0s - loss: 0.1960 - accuracy: 0.9476
13/27 [=============>................] - ETA: 0s - loss: 0.1996 - accuracy: 0.9463
19/27 [====================>.........] - ETA: 0s - loss: 0.2065 - accuracy: 0.9421
25/27 [==========================>...] - ETA: 0s - loss: 0.2137 - accuracy: 0.9376
27/27 [==============================] - 0s 8ms/step - loss: 0.2152 - accuracy: 0.9366

27/27 [==============================] - 0s 16ms/step - loss: 0.2152 - accuracy: 0.9366 - val_loss: 0.7431 - val_accuracy: 0.7493
Epoch 8/50

 1/27 [>.............................] - ETA: 0s - loss: 0.1680 - accuracy: 0.9600
 8/27 [=======>......................] - ETA: 0s - loss: 0.1629 - accuracy: 0.9572
15/27 [===============>..............] - ETA: 0s - loss: 0.1690 - accuracy: 0.9549
22/27 [=======================>......] - ETA: 0s - loss: 0.1759 - accuracy: 0.9518
27/27 [==============================] - 0s 8ms/step - loss: 0.1792 - accuracy: 0.9494

27/27 [==============================] - 0s 15ms/step - loss: 0.1792 - accuracy: 0.9494 - val_loss: 0.7882 - val_accuracy: 0.7504
Epoch 9/50

 1/27 [>.............................] - ETA: 0s - loss: 0.1257 - accuracy: 0.9800
 7/27 [======>.......................] - ETA: 0s - loss: 0.1384 - accuracy: 0.9716
14/27 [==============>...............] - ETA: 0s - loss: 0.1365 - accuracy: 0.9696
21/27 [======================>.......] - ETA: 0s - loss: 0.1413 - accuracy: 0.9661
27/27 [==============================] - 0s 8ms/step - loss: 0.1461 - accuracy: 0.9631

27/27 [==============================] - 0s 15ms/step - loss: 0.1461 - accuracy: 0.9631 - val_loss: 0.8412 - val_accuracy: 0.7501
Epoch 10/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0947 - accuracy: 0.9800
 8/27 [=======>......................] - ETA: 0s - loss: 0.1069 - accuracy: 0.9756
15/27 [===============>..............] - ETA: 0s - loss: 0.1093 - accuracy: 0.9762
22/27 [=======================>......] - ETA: 0s - loss: 0.1130 - accuracy: 0.9745
27/27 [==============================] - 0s 8ms/step - loss: 0.1171 - accuracy: 0.9730

27/27 [==============================] - 0s 15ms/step - loss: 0.1171 - accuracy: 0.9730 - val_loss: 0.9089 - val_accuracy: 0.7369
Epoch 11/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0862 - accuracy: 0.9860
 8/27 [=======>......................] - ETA: 0s - loss: 0.0870 - accuracy: 0.9844
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20/27 [=====================>........] - ETA: 0s - loss: 0.0914 - accuracy: 0.9815
26/27 [===========================>..] - ETA: 0s - loss: 0.0921 - accuracy: 0.9809
27/27 [==============================] - 0s 8ms/step - loss: 0.0919 - accuracy: 0.9809

27/27 [==============================] - 0s 16ms/step - loss: 0.0919 - accuracy: 0.9809 - val_loss: 0.9556 - val_accuracy: 0.7413
Epoch 12/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0635 - accuracy: 0.9920
 8/27 [=======>......................] - ETA: 0s - loss: 0.0627 - accuracy: 0.9905
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20/27 [=====================>........] - ETA: 0s - loss: 0.0678 - accuracy: 0.9886
26/27 [===========================>..] - ETA: 0s - loss: 0.0697 - accuracy: 0.9873
27/27 [==============================] - 0s 9ms/step - loss: 0.0700 - accuracy: 0.9873

27/27 [==============================] - 0s 16ms/step - loss: 0.0700 - accuracy: 0.9873 - val_loss: 1.0103 - val_accuracy: 0.7379
Epoch 13/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0597 - accuracy: 0.9910
 8/27 [=======>......................] - ETA: 0s - loss: 0.0490 - accuracy: 0.9939
15/27 [===============>..............] - ETA: 0s - loss: 0.0518 - accuracy: 0.9929
21/27 [======================>.......] - ETA: 0s - loss: 0.0533 - accuracy: 0.9922
27/27 [==============================] - 0s 8ms/step - loss: 0.0534 - accuracy: 0.9921

27/27 [==============================] - 0s 15ms/step - loss: 0.0534 - accuracy: 0.9921 - val_loss: 1.0794 - val_accuracy: 0.7346
Epoch 14/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0484 - accuracy: 0.9890
 7/27 [======>.......................] - ETA: 0s - loss: 0.0397 - accuracy: 0.9941
13/27 [=============>................] - ETA: 0s - loss: 0.0401 - accuracy: 0.9940
19/27 [====================>.........] - ETA: 0s - loss: 0.0400 - accuracy: 0.9945
26/27 [===========================>..] - ETA: 0s - loss: 0.0411 - accuracy: 0.9944
27/27 [==============================] - 0s 8ms/step - loss: 0.0414 - accuracy: 0.9944

27/27 [==============================] - 0s 16ms/step - loss: 0.0414 - accuracy: 0.9944 - val_loss: 1.1236 - val_accuracy: 0.7337
Epoch 15/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0272 - accuracy: 0.9970
 8/27 [=======>......................] - ETA: 0s - loss: 0.0291 - accuracy: 0.9971
14/27 [==============>...............] - ETA: 0s - loss: 0.0280 - accuracy: 0.9974
20/27 [=====================>........] - ETA: 0s - loss: 0.0302 - accuracy: 0.9967
26/27 [===========================>..] - ETA: 0s - loss: 0.0307 - accuracy: 0.9965
27/27 [==============================] - 0s 8ms/step - loss: 0.0311 - accuracy: 0.9965

27/27 [==============================] - 0s 16ms/step - loss: 0.0311 - accuracy: 0.9965 - val_loss: 1.1729 - val_accuracy: 0.7343
Epoch 16/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0155 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0234 - accuracy: 0.9979
13/27 [=============>................] - ETA: 0s - loss: 0.0241 - accuracy: 0.9975
19/27 [====================>.........] - ETA: 0s - loss: 0.0245 - accuracy: 0.9973
25/27 [==========================>...] - ETA: 0s - loss: 0.0239 - accuracy: 0.9975
27/27 [==============================] - 0s 8ms/step - loss: 0.0240 - accuracy: 0.9975

27/27 [==============================] - 0s 17ms/step - loss: 0.0240 - accuracy: 0.9975 - val_loss: 1.2235 - val_accuracy: 0.7334
Epoch 17/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0164 - accuracy: 0.9990
 7/27 [======>.......................] - ETA: 0s - loss: 0.0165 - accuracy: 0.9989
14/27 [==============>...............] - ETA: 0s - loss: 0.0174 - accuracy: 0.9987
20/27 [=====================>........] - ETA: 0s - loss: 0.0182 - accuracy: 0.9985
26/27 [===========================>..] - ETA: 0s - loss: 0.0191 - accuracy: 0.9983
27/27 [==============================] - 0s 8ms/step - loss: 0.0191 - accuracy: 0.9983

27/27 [==============================] - 0s 15ms/step - loss: 0.0191 - accuracy: 0.9983 - val_loss: 1.2579 - val_accuracy: 0.7312
Epoch 18/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0116 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0141 - accuracy: 0.9990
14/27 [==============>...............] - ETA: 0s - loss: 0.0143 - accuracy: 0.9989
21/27 [======================>.......] - ETA: 0s - loss: 0.0153 - accuracy: 0.9985
27/27 [==============================] - 0s 8ms/step - loss: 0.0156 - accuracy: 0.9985

27/27 [==============================] - 0s 16ms/step - loss: 0.0156 - accuracy: 0.9985 - val_loss: 1.2974 - val_accuracy: 0.7312
Epoch 19/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0104 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0120 - accuracy: 0.9991
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26/27 [===========================>..] - ETA: 0s - loss: 0.0128 - accuracy: 0.9989
27/27 [==============================] - 0s 8ms/step - loss: 0.0128 - accuracy: 0.9989

27/27 [==============================] - 0s 16ms/step - loss: 0.0128 - accuracy: 0.9989 - val_loss: 1.3311 - val_accuracy: 0.7308
Epoch 20/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0079 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0105 - accuracy: 0.9991
14/27 [==============>...............] - ETA: 0s - loss: 0.0109 - accuracy: 0.9991
20/27 [=====================>........] - ETA: 0s - loss: 0.0106 - accuracy: 0.9991
27/27 [==============================] - 0s 8ms/step - loss: 0.0107 - accuracy: 0.9991

27/27 [==============================] - 0s 19ms/step - loss: 0.0107 - accuracy: 0.9991 - val_loss: 1.3629 - val_accuracy: 0.7305
Epoch 21/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0078 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0092 - accuracy: 0.9996
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19/27 [====================>.........] - ETA: 0s - loss: 0.0091 - accuracy: 0.9994
25/27 [==========================>...] - ETA: 0s - loss: 0.0095 - accuracy: 0.9993
27/27 [==============================] - 0s 9ms/step - loss: 0.0094 - accuracy: 0.9994

27/27 [==============================] - 0s 17ms/step - loss: 0.0094 - accuracy: 0.9994 - val_loss: 1.3927 - val_accuracy: 0.7302
Epoch 22/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0058 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0091 - accuracy: 0.9991
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19/27 [====================>.........] - ETA: 0s - loss: 0.0082 - accuracy: 0.9994
26/27 [===========================>..] - ETA: 0s - loss: 0.0082 - accuracy: 0.9993
27/27 [==============================] - 0s 9ms/step - loss: 0.0082 - accuracy: 0.9993

27/27 [==============================] - 0s 16ms/step - loss: 0.0082 - accuracy: 0.9993 - val_loss: 1.4161 - val_accuracy: 0.7305
Epoch 23/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0050 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0064 - accuracy: 0.9996
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25/27 [==========================>...] - ETA: 0s - loss: 0.0070 - accuracy: 0.9994
27/27 [==============================] - 0s 8ms/step - loss: 0.0070 - accuracy: 0.9994

27/27 [==============================] - 0s 16ms/step - loss: 0.0070 - accuracy: 0.9994 - val_loss: 1.4402 - val_accuracy: 0.7306
Epoch 24/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0061 - accuracy: 0.9990
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27/27 [==============================] - 0s 9ms/step - loss: 0.0063 - accuracy: 0.9995

27/27 [==============================] - 0s 16ms/step - loss: 0.0063 - accuracy: 0.9995 - val_loss: 1.4637 - val_accuracy: 0.7287
Epoch 25/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0073 - accuracy: 0.9980
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26/27 [===========================>..] - ETA: 0s - loss: 0.0059 - accuracy: 0.9994
27/27 [==============================] - 0s 9ms/step - loss: 0.0059 - accuracy: 0.9994

27/27 [==============================] - 0s 16ms/step - loss: 0.0059 - accuracy: 0.9994 - val_loss: 1.4852 - val_accuracy: 0.7296
Epoch 26/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0031 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0044 - accuracy: 0.9996
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25/27 [==========================>...] - ETA: 0s - loss: 0.0052 - accuracy: 0.9994
27/27 [==============================] - 0s 9ms/step - loss: 0.0052 - accuracy: 0.9994

27/27 [==============================] - 0s 16ms/step - loss: 0.0052 - accuracy: 0.9994 - val_loss: 1.5046 - val_accuracy: 0.7296
Epoch 27/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0036 - accuracy: 1.0000
 8/27 [=======>......................] - ETA: 0s - loss: 0.0052 - accuracy: 0.9992
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26/27 [===========================>..] - ETA: 0s - loss: 0.0049 - accuracy: 0.9994
27/27 [==============================] - 0s 8ms/step - loss: 0.0049 - accuracy: 0.9994

27/27 [==============================] - 0s 16ms/step - loss: 0.0049 - accuracy: 0.9994 - val_loss: 1.5224 - val_accuracy: 0.7291
Epoch 28/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0029 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0047 - accuracy: 0.9994
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25/27 [==========================>...] - ETA: 0s - loss: 0.0044 - accuracy: 0.9996
27/27 [==============================] - 0s 9ms/step - loss: 0.0045 - accuracy: 0.9995

27/27 [==============================] - 0s 17ms/step - loss: 0.0045 - accuracy: 0.9995 - val_loss: 1.5389 - val_accuracy: 0.7282
Epoch 29/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0031 - accuracy: 1.0000
 6/27 [=====>........................] - ETA: 0s - loss: 0.0039 - accuracy: 0.9997
12/27 [============>.................] - ETA: 0s - loss: 0.0040 - accuracy: 0.9996
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27/27 [==============================] - 0s 9ms/step - loss: 0.0041 - accuracy: 0.9995

27/27 [==============================] - 0s 17ms/step - loss: 0.0041 - accuracy: 0.9995 - val_loss: 1.5572 - val_accuracy: 0.7290
Epoch 30/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0027 - accuracy: 1.0000
 6/27 [=====>........................] - ETA: 0s - loss: 0.0040 - accuracy: 0.9997
12/27 [============>.................] - ETA: 0s - loss: 0.0036 - accuracy: 0.9998
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27/27 [==============================] - 0s 9ms/step - loss: 0.0039 - accuracy: 0.9996

27/27 [==============================] - 0s 16ms/step - loss: 0.0039 - accuracy: 0.9996 - val_loss: 1.5711 - val_accuracy: 0.7284
Epoch 31/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0022 - accuracy: 1.0000
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27/27 [==============================] - 0s 10ms/step - loss: 0.0037 - accuracy: 0.9995

27/27 [==============================] - 0s 17ms/step - loss: 0.0037 - accuracy: 0.9995 - val_loss: 1.5878 - val_accuracy: 0.7284
Epoch 32/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0034 - accuracy: 0.9990
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21/27 [======================>.......] - ETA: 0s - loss: 0.0034 - accuracy: 0.9996
27/27 [==============================] - 0s 8ms/step - loss: 0.0034 - accuracy: 0.9996

27/27 [==============================] - 0s 16ms/step - loss: 0.0034 - accuracy: 0.9996 - val_loss: 1.6054 - val_accuracy: 0.7288
Epoch 33/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0020 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0034 - accuracy: 0.9994
13/27 [=============>................] - ETA: 0s - loss: 0.0033 - accuracy: 0.9995
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25/27 [==========================>...] - ETA: 0s - loss: 0.0033 - accuracy: 0.9995
27/27 [==============================] - 0s 9ms/step - loss: 0.0033 - accuracy: 0.9995

27/27 [==============================] - 0s 16ms/step - loss: 0.0033 - accuracy: 0.9995 - val_loss: 1.6171 - val_accuracy: 0.7281
Epoch 34/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0021 - accuracy: 1.0000
 6/27 [=====>........................] - ETA: 0s - loss: 0.0033 - accuracy: 0.9995
11/27 [===========>..................] - ETA: 0s - loss: 0.0030 - accuracy: 0.9996
17/27 [=================>............] - ETA: 0s - loss: 0.0027 - accuracy: 0.9997
23/27 [========================>.....] - ETA: 0s - loss: 0.0029 - accuracy: 0.9996
27/27 [==============================] - 0s 9ms/step - loss: 0.0030 - accuracy: 0.9996

27/27 [==============================] - 0s 17ms/step - loss: 0.0030 - accuracy: 0.9996 - val_loss: 1.6300 - val_accuracy: 0.7290
Epoch 35/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0018 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0027 - accuracy: 0.9997
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25/27 [==========================>...] - ETA: 0s - loss: 0.0031 - accuracy: 0.9995
27/27 [==============================] - 0s 9ms/step - loss: 0.0032 - accuracy: 0.9995

27/27 [==============================] - 0s 17ms/step - loss: 0.0032 - accuracy: 0.9995 - val_loss: 1.6449 - val_accuracy: 0.7291
Epoch 36/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0020 - accuracy: 1.0000
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19/27 [====================>.........] - ETA: 0s - loss: 0.0038 - accuracy: 0.9996
26/27 [===========================>..] - ETA: 0s - loss: 0.0037 - accuracy: 0.9995
27/27 [==============================] - 0s 9ms/step - loss: 0.0037 - accuracy: 0.9995

27/27 [==============================] - 0s 16ms/step - loss: 0.0037 - accuracy: 0.9995 - val_loss: 1.6599 - val_accuracy: 0.7261
Epoch 37/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0043 - accuracy: 0.9990
 6/27 [=====>........................] - ETA: 0s - loss: 0.0023 - accuracy: 0.9998
12/27 [============>.................] - ETA: 0s - loss: 0.0034 - accuracy: 0.9993
18/27 [===================>..........] - ETA: 0s - loss: 0.0034 - accuracy: 0.9993
24/27 [=========================>....] - ETA: 0s - loss: 0.0032 - accuracy: 0.9994
27/27 [==============================] - 0s 9ms/step - loss: 0.0031 - accuracy: 0.9994

27/27 [==============================] - 0s 16ms/step - loss: 0.0031 - accuracy: 0.9994 - val_loss: 1.6638 - val_accuracy: 0.7299
Epoch 38/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0018 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0026 - accuracy: 0.9994
13/27 [=============>................] - ETA: 0s - loss: 0.0024 - accuracy: 0.9996
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26/27 [===========================>..] - ETA: 0s - loss: 0.0026 - accuracy: 0.9996
27/27 [==============================] - 0s 8ms/step - loss: 0.0026 - accuracy: 0.9996

27/27 [==============================] - 0s 16ms/step - loss: 0.0026 - accuracy: 0.9996 - val_loss: 1.6781 - val_accuracy: 0.7281
Epoch 39/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0014 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0019 - accuracy: 0.9999
13/27 [=============>................] - ETA: 0s - loss: 0.0024 - accuracy: 0.9997
19/27 [====================>.........] - ETA: 0s - loss: 0.0026 - accuracy: 0.9996
25/27 [==========================>...] - ETA: 0s - loss: 0.0025 - accuracy: 0.9996
27/27 [==============================] - 0s 9ms/step - loss: 0.0025 - accuracy: 0.9996

27/27 [==============================] - 0s 16ms/step - loss: 0.0025 - accuracy: 0.9996 - val_loss: 1.6901 - val_accuracy: 0.7278
Epoch 40/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0064 - accuracy: 0.9980
 7/27 [======>.......................] - ETA: 0s - loss: 0.0027 - accuracy: 0.9994
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19/27 [====================>.........] - ETA: 0s - loss: 0.0025 - accuracy: 0.9995
25/27 [==========================>...] - ETA: 0s - loss: 0.0023 - accuracy: 0.9996
27/27 [==============================] - 0s 9ms/step - loss: 0.0023 - accuracy: 0.9996

27/27 [==============================] - 1s 20ms/step - loss: 0.0023 - accuracy: 0.9996 - val_loss: 1.7012 - val_accuracy: 0.7284
Epoch 41/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0037 - accuracy: 0.9990
 7/27 [======>.......................] - ETA: 0s - loss: 0.0023 - accuracy: 0.9996
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20/27 [=====================>........] - ETA: 0s - loss: 0.0023 - accuracy: 0.9996
26/27 [===========================>..] - ETA: 0s - loss: 0.0022 - accuracy: 0.9996
27/27 [==============================] - 0s 8ms/step - loss: 0.0022 - accuracy: 0.9996

27/27 [==============================] - 0s 15ms/step - loss: 0.0022 - accuracy: 0.9996 - val_loss: 1.7112 - val_accuracy: 0.7291
Epoch 42/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0033 - accuracy: 0.9990
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24/27 [=========================>....] - ETA: 0s - loss: 0.0022 - accuracy: 0.9995
27/27 [==============================] - 0s 9ms/step - loss: 0.0022 - accuracy: 0.9995

27/27 [==============================] - 0s 17ms/step - loss: 0.0022 - accuracy: 0.9995 - val_loss: 1.7279 - val_accuracy: 0.7275
Epoch 43/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0010 - accuracy: 1.0000
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26/27 [===========================>..] - ETA: 0s - loss: 0.0019 - accuracy: 0.9996
27/27 [==============================] - 0s 8ms/step - loss: 0.0019 - accuracy: 0.9996

27/27 [==============================] - 0s 16ms/step - loss: 0.0019 - accuracy: 0.9996 - val_loss: 1.7360 - val_accuracy: 0.7279
Epoch 44/50

 1/27 [>.............................] - ETA: 0s - loss: 8.7474e-04 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0018 - accuracy: 0.9997    
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19/27 [====================>.........] - ETA: 0s - loss: 0.0022 - accuracy: 0.9994
25/27 [==========================>...] - ETA: 0s - loss: 0.0020 - accuracy: 0.9996
27/27 [==============================] - 0s 9ms/step - loss: 0.0020 - accuracy: 0.9996

27/27 [==============================] - 0s 16ms/step - loss: 0.0020 - accuracy: 0.9996 - val_loss: 1.7488 - val_accuracy: 0.7270
Epoch 45/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0011 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0021 - accuracy: 0.9994
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25/27 [==========================>...] - ETA: 0s - loss: 0.0019 - accuracy: 0.9995
27/27 [==============================] - 0s 9ms/step - loss: 0.0019 - accuracy: 0.9995

27/27 [==============================] - 0s 16ms/step - loss: 0.0019 - accuracy: 0.9995 - val_loss: 1.7556 - val_accuracy: 0.7273
Epoch 46/50

 1/27 [>.............................] - ETA: 0s - loss: 8.3446e-04 - accuracy: 1.0000
 6/27 [=====>........................] - ETA: 0s - loss: 0.0016 - accuracy: 0.9997    
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27/27 [==============================] - 0s 9ms/step - loss: 0.0018 - accuracy: 0.9996

27/27 [==============================] - 0s 16ms/step - loss: 0.0018 - accuracy: 0.9996 - val_loss: 1.7639 - val_accuracy: 0.7270
Epoch 47/50

 1/27 [>.............................] - ETA: 0s - loss: 9.8285e-04 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0015 - accuracy: 0.9997    
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18/27 [===================>..........] - ETA: 0s - loss: 0.0018 - accuracy: 0.9996
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27/27 [==============================] - 0s 9ms/step - loss: 0.0018 - accuracy: 0.9996

27/27 [==============================] - 0s 17ms/step - loss: 0.0018 - accuracy: 0.9996 - val_loss: 1.7730 - val_accuracy: 0.7287
Epoch 48/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0012 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0019 - accuracy: 0.9994
14/27 [==============>...............] - ETA: 0s - loss: 0.0017 - accuracy: 0.9996
20/27 [=====================>........] - ETA: 0s - loss: 0.0018 - accuracy: 0.9995
26/27 [===========================>..] - ETA: 0s - loss: 0.0018 - accuracy: 0.9996
27/27 [==============================] - 0s 8ms/step - loss: 0.0018 - accuracy: 0.9996

27/27 [==============================] - 0s 16ms/step - loss: 0.0018 - accuracy: 0.9996 - val_loss: 1.7823 - val_accuracy: 0.7278
Epoch 49/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0018 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0026 - accuracy: 0.9993
13/27 [=============>................] - ETA: 0s - loss: 0.0020 - accuracy: 0.9995
19/27 [====================>.........] - ETA: 0s - loss: 0.0018 - accuracy: 0.9996
25/27 [==========================>...] - ETA: 0s - loss: 0.0018 - accuracy: 0.9996
27/27 [==============================] - 0s 9ms/step - loss: 0.0018 - accuracy: 0.9996

27/27 [==============================] - 0s 17ms/step - loss: 0.0018 - accuracy: 0.9996 - val_loss: 1.7927 - val_accuracy: 0.7261
Epoch 50/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0014 - accuracy: 1.0000
 7/27 [======>.......................] - ETA: 0s - loss: 0.0014 - accuracy: 0.9999
14/27 [==============>...............] - ETA: 0s - loss: 0.0016 - accuracy: 0.9997
22/27 [=======================>......] - ETA: 0s - loss: 0.0015 - accuracy: 0.9998
27/27 [==============================] - 0s 7ms/step - loss: 0.0016 - accuracy: 0.9997

27/27 [==============================] - 0s 15ms/step - loss: 0.0016 - accuracy: 0.9997 - val_loss: 1.8040 - val_accuracy: 0.7276

Run completed: runs/2023-03-31T02-08-09Z

Training run 7/9 (flags = list(128, 0.05, 1000, 50, "relu")) 
Using run directory runs/2023-03-31T02-08-32Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 5000) %>%
+   layer_dense(units = FLAGS$nodes, activatio .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('accuracy .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   covid_train_dtm,covid_train$Sentiment, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(covid_valid_d .... [TRUNCATED] 
Epoch 1/50

 1/27 [>.............................] - ETA: 9s - loss: 1.0638 - accuracy: 0.4010
 6/27 [=====>........................] - ETA: 0s - loss: 1.0986 - accuracy: 0.4342
11/27 [===========>..................] - ETA: 0s - loss: 1.0373 - accuracy: 0.4800
16/27 [================>.............] - ETA: 0s - loss: 0.9910 - accuracy: 0.5153
21/27 [======================>.......] - ETA: 0s - loss: 0.9544 - accuracy: 0.5437
26/27 [===========================>..] - ETA: 0s - loss: 0.9245 - accuracy: 0.5635
27/27 [==============================] - 1s 11ms/step - loss: 0.9217 - accuracy: 0.5655

27/27 [==============================] - 1s 37ms/step - loss: 0.9217 - accuracy: 0.5655 - val_loss: 0.7617 - val_accuracy: 0.6652
Epoch 2/50

 1/27 [>.............................] - ETA: 0s - loss: 0.6395 - accuracy: 0.7590
 5/27 [====>.........................] - ETA: 0s - loss: 0.6521 - accuracy: 0.7544
 9/27 [=========>....................] - ETA: 0s - loss: 0.6358 - accuracy: 0.7594
14/27 [==============>...............] - ETA: 0s - loss: 0.6189 - accuracy: 0.7651
18/27 [===================>..........] - ETA: 0s - loss: 0.6156 - accuracy: 0.7640
22/27 [=======================>......] - ETA: 0s - loss: 0.6097 - accuracy: 0.7666
26/27 [===========================>..] - ETA: 0s - loss: 0.6027 - accuracy: 0.7687
27/27 [==============================] - 0s 13ms/step - loss: 0.6017 - accuracy: 0.7696

27/27 [==============================] - 1s 21ms/step - loss: 0.6017 - accuracy: 0.7696 - val_loss: 0.6661 - val_accuracy: 0.7322
Epoch 3/50

 1/27 [>.............................] - ETA: 0s - loss: 0.4403 - accuracy: 0.8520
 6/27 [=====>........................] - ETA: 0s - loss: 0.4441 - accuracy: 0.8497
11/27 [===========>..................] - ETA: 0s - loss: 0.4421 - accuracy: 0.8488
16/27 [================>.............] - ETA: 0s - loss: 0.4395 - accuracy: 0.8468
21/27 [======================>.......] - ETA: 0s - loss: 0.4405 - accuracy: 0.8450
25/27 [==========================>...] - ETA: 0s - loss: 0.4462 - accuracy: 0.8410
27/27 [==============================] - 0s 12ms/step - loss: 0.4482 - accuracy: 0.8403

27/27 [==============================] - 1s 19ms/step - loss: 0.4482 - accuracy: 0.8403 - val_loss: 0.6704 - val_accuracy: 0.7423
Epoch 4/50

 1/27 [>.............................] - ETA: 0s - loss: 0.3666 - accuracy: 0.8830
 5/27 [====>.........................] - ETA: 0s - loss: 0.3388 - accuracy: 0.8948
10/27 [==========>...................] - ETA: 0s - loss: 0.3365 - accuracy: 0.8923
15/27 [===============>..............] - ETA: 0s - loss: 0.3340 - accuracy: 0.8914
19/27 [====================>.........] - ETA: 0s - loss: 0.3330 - accuracy: 0.8908
23/27 [========================>.....] - ETA: 0s - loss: 0.3367 - accuracy: 0.8883
27/27 [==============================] - 0s 12ms/step - loss: 0.3398 - accuracy: 0.8865

27/27 [==============================] - 1s 20ms/step - loss: 0.3398 - accuracy: 0.8865 - val_loss: 0.6908 - val_accuracy: 0.7467
Epoch 5/50

 1/27 [>.............................] - ETA: 0s - loss: 0.2618 - accuracy: 0.9190
 6/27 [=====>........................] - ETA: 0s - loss: 0.2367 - accuracy: 0.9350
11/27 [===========>..................] - ETA: 0s - loss: 0.2256 - accuracy: 0.9369
16/27 [================>.............] - ETA: 0s - loss: 0.2282 - accuracy: 0.9336
21/27 [======================>.......] - ETA: 0s - loss: 0.2285 - accuracy: 0.9305
25/27 [==========================>...] - ETA: 0s - loss: 0.2323 - accuracy: 0.9280
27/27 [==============================] - 0s 12ms/step - loss: 0.2331 - accuracy: 0.9276

27/27 [==============================] - 1s 19ms/step - loss: 0.2331 - accuracy: 0.9276 - val_loss: 0.7710 - val_accuracy: 0.7388
Epoch 6/50

 1/27 [>.............................] - ETA: 0s - loss: 0.1301 - accuracy: 0.9730
 6/27 [=====>........................] - ETA: 0s - loss: 0.1429 - accuracy: 0.9645
11/27 [===========>..................] - ETA: 0s - loss: 0.1418 - accuracy: 0.9641
16/27 [================>.............] - ETA: 0s - loss: 0.1375 - accuracy: 0.9643
20/27 [=====================>........] - ETA: 0s - loss: 0.1390 - accuracy: 0.9630
24/27 [=========================>....] - ETA: 0s - loss: 0.1410 - accuracy: 0.9614
27/27 [==============================] - 0s 12ms/step - loss: 0.1411 - accuracy: 0.9610

27/27 [==============================] - 1s 29ms/step - loss: 0.1411 - accuracy: 0.9610 - val_loss: 0.8631 - val_accuracy: 0.7402
Epoch 7/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0958 - accuracy: 0.9800
 6/27 [=====>........................] - ETA: 0s - loss: 0.0778 - accuracy: 0.9865
11/27 [===========>..................] - ETA: 0s - loss: 0.0745 - accuracy: 0.9857
16/27 [================>.............] - ETA: 0s - loss: 0.0735 - accuracy: 0.9849
21/27 [======================>.......] - ETA: 0s - loss: 0.0738 - accuracy: 0.9841
26/27 [===========================>..] - ETA: 0s - loss: 0.0739 - accuracy: 0.9834
27/27 [==============================] - 0s 11ms/step - loss: 0.0739 - accuracy: 0.9833

27/27 [==============================] - 1s 19ms/step - loss: 0.0739 - accuracy: 0.9833 - val_loss: 0.9794 - val_accuracy: 0.7408
Epoch 8/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0342 - accuracy: 0.9950
 6/27 [=====>........................] - ETA: 0s - loss: 0.0377 - accuracy: 0.9948
10/27 [==========>...................] - ETA: 0s - loss: 0.0368 - accuracy: 0.9939
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20/27 [=====================>........] - ETA: 0s - loss: 0.0369 - accuracy: 0.9934
25/27 [==========================>...] - ETA: 0s - loss: 0.0367 - accuracy: 0.9934
27/27 [==============================] - 0s 12ms/step - loss: 0.0368 - accuracy: 0.9932

27/27 [==============================] - 1s 20ms/step - loss: 0.0368 - accuracy: 0.9932 - val_loss: 1.1013 - val_accuracy: 0.7367
Epoch 9/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0242 - accuracy: 0.9970
 5/27 [====>.........................] - ETA: 0s - loss: 0.0219 - accuracy: 0.9962
 9/27 [=========>....................] - ETA: 0s - loss: 0.0226 - accuracy: 0.9963
14/27 [==============>...............] - ETA: 0s - loss: 0.0212 - accuracy: 0.9967
18/27 [===================>..........] - ETA: 0s - loss: 0.0202 - accuracy: 0.9973
22/27 [=======================>......] - ETA: 0s - loss: 0.0200 - accuracy: 0.9970
27/27 [==============================] - 0s 12ms/step - loss: 0.0206 - accuracy: 0.9968

27/27 [==============================] - 1s 20ms/step - loss: 0.0206 - accuracy: 0.9968 - val_loss: 1.2005 - val_accuracy: 0.7341
Epoch 10/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0099 - accuracy: 0.9990
 6/27 [=====>........................] - ETA: 0s - loss: 0.0113 - accuracy: 0.9990
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16/27 [================>.............] - ETA: 0s - loss: 0.0125 - accuracy: 0.9982
21/27 [======================>.......] - ETA: 0s - loss: 0.0120 - accuracy: 0.9983
26/27 [===========================>..] - ETA: 0s - loss: 0.0120 - accuracy: 0.9983
27/27 [==============================] - 0s 11ms/step - loss: 0.0120 - accuracy: 0.9983

27/27 [==============================] - 0s 19ms/step - loss: 0.0120 - accuracy: 0.9983 - val_loss: 1.3071 - val_accuracy: 0.7361
Epoch 11/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0108 - accuracy: 0.9970
 6/27 [=====>........................] - ETA: 0s - loss: 0.0080 - accuracy: 0.9987
11/27 [===========>..................] - ETA: 0s - loss: 0.0084 - accuracy: 0.9985
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21/27 [======================>.......] - ETA: 0s - loss: 0.0079 - accuracy: 0.9988
26/27 [===========================>..] - ETA: 0s - loss: 0.0081 - accuracy: 0.9988
27/27 [==============================] - 0s 11ms/step - loss: 0.0080 - accuracy: 0.9988

27/27 [==============================] - 0s 18ms/step - loss: 0.0080 - accuracy: 0.9988 - val_loss: 1.3639 - val_accuracy: 0.7346
Epoch 12/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0062 - accuracy: 0.9990
 6/27 [=====>........................] - ETA: 0s - loss: 0.0063 - accuracy: 0.9990
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21/27 [======================>.......] - ETA: 0s - loss: 0.0062 - accuracy: 0.9990
26/27 [===========================>..] - ETA: 0s - loss: 0.0057 - accuracy: 0.9992
27/27 [==============================] - 0s 11ms/step - loss: 0.0058 - accuracy: 0.9992

27/27 [==============================] - 0s 18ms/step - loss: 0.0058 - accuracy: 0.9992 - val_loss: 1.4147 - val_accuracy: 0.7344
Epoch 13/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0024 - accuracy: 1.0000
 5/27 [====>.........................] - ETA: 0s - loss: 0.0034 - accuracy: 0.9996
10/27 [==========>...................] - ETA: 0s - loss: 0.0033 - accuracy: 0.9997
15/27 [===============>..............] - ETA: 0s - loss: 0.0035 - accuracy: 0.9997
20/27 [=====================>........] - ETA: 0s - loss: 0.0036 - accuracy: 0.9996
25/27 [==========================>...] - ETA: 0s - loss: 0.0042 - accuracy: 0.9994
27/27 [==============================] - 0s 11ms/step - loss: 0.0042 - accuracy: 0.9994

27/27 [==============================] - 1s 19ms/step - loss: 0.0042 - accuracy: 0.9994 - val_loss: 1.4624 - val_accuracy: 0.7350
Epoch 14/50

 1/27 [>.............................] - ETA: 0s - loss: 0.0045 - accuracy: 0.9990
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11/27 [===========>..................] - ETA: 0s - loss: 0.0042 - accuracy: 0.9993
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27/27 [==============================] - 0s 12ms/step - loss: 0.0042 - accuracy: 0.9993

27/27 [==============================] - 1s 19ms/step - loss: 0.0042 - accuracy: 0.9993 - val_loss: 1.5063 - val_accuracy: 0.7337
Epoch 15/50

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27/27 [==============================] - 0s 12ms/step - loss: 0.0030 - accuracy: 0.9994

27/27 [==============================] - 1s 21ms/step - loss: 0.0030 - accuracy: 0.9994 - val_loss: 1.5418 - val_accuracy: 0.7312
Epoch 16/50

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27/27 [==============================] - 0s 11ms/step - loss: 0.0031 - accuracy: 0.9994

27/27 [==============================] - 1s 19ms/step - loss: 0.0031 - accuracy: 0.9994 - val_loss: 1.5662 - val_accuracy: 0.7337
Epoch 17/50

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27/27 [==============================] - 0s 11ms/step - loss: 0.0023 - accuracy: 0.9995

27/27 [==============================] - 1s 19ms/step - loss: 0.0023 - accuracy: 0.9995 - val_loss: 1.5921 - val_accuracy: 0.7340
Epoch 18/50

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27/27 [==============================] - 0s 12ms/step - loss: 0.0032 - accuracy: 0.9994

27/27 [==============================] - 1s 22ms/step - loss: 0.0032 - accuracy: 0.9994 - val_loss: 1.5982 - val_accuracy: 0.7305
Epoch 19/50

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27/27 [==============================] - 0s 12ms/step - loss: 0.0019 - accuracy: 0.9995

27/27 [==============================] - 1s 20ms/step - loss: 0.0019 - accuracy: 0.9995 - val_loss: 1.6661 - val_accuracy: 0.7312
Epoch 20/50

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27/27 [==============================] - 0s 11ms/step - loss: 0.0018 - accuracy: 0.9995

27/27 [==============================] - 0s 19ms/step - loss: 0.0018 - accuracy: 0.9995 - val_loss: 1.6690 - val_accuracy: 0.7305
Epoch 21/50

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27/27 [==============================] - 0s 13ms/step - loss: 0.0017 - accuracy: 0.9996

27/27 [==============================] - 1s 21ms/step - loss: 0.0017 - accuracy: 0.9996 - val_loss: 1.6923 - val_accuracy: 0.7323
Epoch 22/50

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27/27 [==============================] - 0s 11ms/step - loss: 0.0018 - accuracy: 0.9996

27/27 [==============================] - 1s 19ms/step - loss: 0.0018 - accuracy: 0.9996 - val_loss: 1.7150 - val_accuracy: 0.7282
Epoch 23/50

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27/27 [==============================] - 0s 12ms/step - loss: 0.0019 - accuracy: 0.9995

27/27 [==============================] - 1s 19ms/step - loss: 0.0019 - accuracy: 0.9995 - val_loss: 1.7493 - val_accuracy: 0.7291
Epoch 24/50

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27/27 [==============================] - 0s 13ms/step - loss: 0.0016 - accuracy: 0.9996

27/27 [==============================] - 1s 20ms/step - loss: 0.0016 - accuracy: 0.9996 - val_loss: 1.7563 - val_accuracy: 0.7323
Epoch 25/50

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27/27 [==============================] - 0s 13ms/step - loss: 0.0014 - accuracy: 0.9997

27/27 [==============================] - 1s 21ms/step - loss: 0.0014 - accuracy: 0.9997 - val_loss: 1.7725 - val_accuracy: 0.7306
Epoch 26/50

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27/27 [==============================] - 0s 12ms/step - loss: 0.0014 - accuracy: 0.9996

27/27 [==============================] - 1s 19ms/step - loss: 0.0014 - accuracy: 0.9996 - val_loss: 1.7887 - val_accuracy: 0.7335
Epoch 27/50

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27/27 [==============================] - 0s 12ms/step - loss: 0.0017 - accuracy: 0.9996

27/27 [==============================] - 1s 20ms/step - loss: 0.0017 - accuracy: 0.9996 - val_loss: 1.8021 - val_accuracy: 0.7322
Epoch 28/50

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27/27 [==============================] - 0s 13ms/step - loss: 0.0017 - accuracy: 0.9995

27/27 [==============================] - 1s 20ms/step - loss: 0.0017 - accuracy: 0.9995 - val_loss: 1.8151 - val_accuracy: 0.7311
Epoch 29/50

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27/27 [==============================] - 0s 13ms/step - loss: 0.0013 - accuracy: 0.9996

27/27 [==============================] - 1s 21ms/step - loss: 0.0013 - accuracy: 0.9996 - val_loss: 1.8320 - val_accuracy: 0.7325
Epoch 30/50

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27/27 [==============================] - 0s 13ms/step - loss: 0.0015 - accuracy: 0.9997

27/27 [==============================] - 1s 20ms/step - loss: 0.0015 - accuracy: 0.9997 - val_loss: 1.8802 - val_accuracy: 0.7296
Epoch 31/50

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27/27 [==============================] - 0s 11ms/step - loss: 0.0014 - accuracy: 0.9996

27/27 [==============================] - 0s 18ms/step - loss: 0.0014 - accuracy: 0.9996 - val_loss: 1.8529 - val_accuracy: 0.7308
Epoch 32/50

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27/27 [==============================] - 0s 11ms/step - loss: 0.0011 - accuracy: 0.9997

27/27 [==============================] - 1s 19ms/step - loss: 0.0011 - accuracy: 0.9997 - val_loss: 1.9071 - val_accuracy: 0.7243
Epoch 33/50

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27/27 [==============================] - 0s 12ms/step - loss: 9.6240e-04 - accuracy: 0.9997

27/27 [==============================] - 1s 20ms/step - loss: 9.6240e-04 - accuracy: 0.9997 - val_loss: 1.8790 - val_accuracy: 0.7325
Epoch 34/50

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27/27 [==============================] - 0s 12ms/step - loss: 0.0010 - accuracy: 0.9997

27/27 [==============================] - 1s 20ms/step - loss: 0.0010 - accuracy: 0.9997 - val_loss: 1.9316 - val_accuracy: 0.7297
Epoch 35/50

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27/27 [==============================] - 0s 13ms/step - loss: 0.0016 - accuracy: 0.9995

27/27 [==============================] - 1s 21ms/step - loss: 0.0016 - accuracy: 0.9995 - val_loss: 1.9599 - val_accuracy: 0.7262
Epoch 36/50

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27/27 [==============================] - 0s 11ms/step - loss: 9.4031e-04 - accuracy: 0.9997

27/27 [==============================] - 1s 19ms/step - loss: 9.4031e-04 - accuracy: 0.9997 - val_loss: 1.9224 - val_accuracy: 0.7309
Epoch 37/50

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27/27 [==============================] - 0s 11ms/step - loss: 8.5363e-04 - accuracy: 0.9997

27/27 [==============================] - 1s 20ms/step - loss: 8.5363e-04 - accuracy: 0.9997 - val_loss: 1.9471 - val_accuracy: 0.7305
Epoch 38/50

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27/27 [==============================] - 0s 11ms/step - loss: 0.0013 - accuracy: 0.9997

27/27 [==============================] - 0s 19ms/step - loss: 0.0013 - accuracy: 0.9997 - val_loss: 1.9635 - val_accuracy: 0.7284
Epoch 39/50

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27/27 [==============================] - 0s 11ms/step - loss: 0.0012 - accuracy: 0.9997

27/27 [==============================] - 0s 18ms/step - loss: 0.0012 - accuracy: 0.9997 - val_loss: 1.9869 - val_accuracy: 0.7296
Epoch 40/50

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27/27 [==============================] - 0s 11ms/step - loss: 9.4628e-04 - accuracy: 0.9997

27/27 [==============================] - 1s 19ms/step - loss: 9.4628e-04 - accuracy: 0.9997 - val_loss: 1.9908 - val_accuracy: 0.7262
Epoch 41/50

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27/27 [==============================] - 0s 11ms/step - loss: 8.5378e-04 - accuracy: 0.9997

27/27 [==============================] - 0s 18ms/step - loss: 8.5378e-04 - accuracy: 0.9997 - val_loss: 2.0300 - val_accuracy: 0.7267
Epoch 42/50

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27/27 [==============================] - 0s 14ms/step - loss: 7.5497e-04 - accuracy: 0.9998

27/27 [==============================] - 1s 21ms/step - loss: 7.5497e-04 - accuracy: 0.9998 - val_loss: 2.0265 - val_accuracy: 0.7296
Epoch 43/50

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27/27 [==============================] - 0s 13ms/step - loss: 7.5730e-04 - accuracy: 0.9997

27/27 [==============================] - 1s 21ms/step - loss: 7.5730e-04 - accuracy: 0.9997 - val_loss: 2.0264 - val_accuracy: 0.7319
Epoch 44/50

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27/27 [==============================] - 0s 13ms/step - loss: 6.9752e-04 - accuracy: 0.9997

27/27 [==============================] - 1s 22ms/step - loss: 6.9752e-04 - accuracy: 0.9997 - val_loss: 2.0745 - val_accuracy: 0.7250
Epoch 45/50

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27/27 [==============================] - 0s 12ms/step - loss: 6.5392e-04 - accuracy: 0.9998

27/27 [==============================] - 1s 20ms/step - loss: 6.5392e-04 - accuracy: 0.9998 - val_loss: 2.0856 - val_accuracy: 0.7294
Epoch 46/50

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27/27 [==============================] - 0s 11ms/step - loss: 7.6498e-04 - accuracy: 0.9997

27/27 [==============================] - 1s 23ms/step - loss: 7.6498e-04 - accuracy: 0.9997 - val_loss: 2.0675 - val_accuracy: 0.7299
Epoch 47/50

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27/27 [==============================] - 0s 11ms/step - loss: 6.7044e-04 - accuracy: 0.9997

27/27 [==============================] - 1s 19ms/step - loss: 6.7044e-04 - accuracy: 0.9997 - val_loss: 2.1010 - val_accuracy: 0.7262
Epoch 48/50

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27/27 [==============================] - 0s 12ms/step - loss: 7.0900e-04 - accuracy: 0.9997

27/27 [==============================] - 1s 21ms/step - loss: 7.0900e-04 - accuracy: 0.9997 - val_loss: 2.0854 - val_accuracy: 0.7276
Epoch 49/50

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27/27 [==============================] - 0s 16ms/step - loss: 7.3456e-04 - accuracy: 0.9997

27/27 [==============================] - 1s 24ms/step - loss: 7.3456e-04 - accuracy: 0.9997 - val_loss: 2.0988 - val_accuracy: 0.7312
Epoch 50/50

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27/27 [==============================] - 0s 12ms/step - loss: 6.6342e-04 - accuracy: 0.9998

27/27 [==============================] - 1s 19ms/step - loss: 6.6342e-04 - accuracy: 0.9998 - val_loss: 2.1108 - val_accuracy: 0.7279

Run completed: runs/2023-03-31T02-08-32Z

Training run 8/9 (flags = list(64, 0.01, 100, 30, "tanh")) 
Using run directory runs/2023-03-31T02-08-59Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 5000) %>%
+   layer_dense(units = FLAGS$nodes, activatio .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('accuracy .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   covid_train_dtm,covid_train$Sentiment, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(covid_valid_d .... [TRUNCATED] 
Epoch 1/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.7180 - accuracy: 0.6905

264/264 [==============================] - 2s 6ms/step - loss: 0.7180 - accuracy: 0.6905 - val_loss: 0.6030 - val_accuracy: 0.7560
Epoch 2/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.4426 - accuracy: 0.8352

264/264 [==============================] - 1s 4ms/step - loss: 0.4426 - accuracy: 0.8352 - val_loss: 0.5956 - val_accuracy: 0.7691
Epoch 3/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.3212 - accuracy: 0.8836

264/264 [==============================] - 1s 4ms/step - loss: 0.3212 - accuracy: 0.8836 - val_loss: 0.6385 - val_accuracy: 0.7637
Epoch 4/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.2161 - accuracy: 0.9256

264/264 [==============================] - 1s 4ms/step - loss: 0.2161 - accuracy: 0.9256 - val_loss: 0.7564 - val_accuracy: 0.7581
Epoch 5/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.1305 - accuracy: 0.9584 - val_loss: 0.8733 - val_accuracy: 0.7546
Epoch 6/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0683 - accuracy: 0.9828

264/264 [==============================] - 1s 4ms/step - loss: 0.0683 - accuracy: 0.9828 - val_loss: 1.0446 - val_accuracy: 0.7461
Epoch 7/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0344 - accuracy: 0.9924

264/264 [==============================] - 1s 4ms/step - loss: 0.0344 - accuracy: 0.9924 - val_loss: 1.1790 - val_accuracy: 0.7502
Epoch 8/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0178 - accuracy: 0.9967 - val_loss: 1.3131 - val_accuracy: 0.7460
Epoch 9/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0124 - accuracy: 0.9974 - val_loss: 1.4189 - val_accuracy: 0.7446
Epoch 10/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0083 - accuracy: 0.9982

264/264 [==============================] - 1s 4ms/step - loss: 0.0083 - accuracy: 0.9982 - val_loss: 1.5268 - val_accuracy: 0.7434
Epoch 11/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0091 - accuracy: 0.9983

264/264 [==============================] - 1s 4ms/step - loss: 0.0091 - accuracy: 0.9983 - val_loss: 1.5915 - val_accuracy: 0.7411
Epoch 12/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0074 - accuracy: 0.9983 - val_loss: 1.5753 - val_accuracy: 0.7390
Epoch 13/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0390 - accuracy: 0.9867

264/264 [==============================] - 1s 4ms/step - loss: 0.0390 - accuracy: 0.9867 - val_loss: 1.5635 - val_accuracy: 0.7255
Epoch 14/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0341 - accuracy: 0.9888 - val_loss: 1.5588 - val_accuracy: 0.7326
Epoch 15/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0119 - accuracy: 0.9969

264/264 [==============================] - 1s 4ms/step - loss: 0.0119 - accuracy: 0.9969 - val_loss: 1.6841 - val_accuracy: 0.7326
Epoch 16/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0058 - accuracy: 0.9988 - val_loss: 1.7640 - val_accuracy: 0.7346
Epoch 17/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0036 - accuracy: 0.9991 - val_loss: 1.7837 - val_accuracy: 0.7402
Epoch 18/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0028 - accuracy: 0.9992 - val_loss: 1.8636 - val_accuracy: 0.7353
Epoch 19/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0032 - accuracy: 0.9991 - val_loss: 1.9325 - val_accuracy: 0.7373
Epoch 20/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0019 - accuracy: 0.9994 - val_loss: 1.9550 - val_accuracy: 0.7328
Epoch 21/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0030 - accuracy: 0.9991 - val_loss: 1.9983 - val_accuracy: 0.7378
Epoch 22/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0036 - accuracy: 0.9989 - val_loss: 1.9906 - val_accuracy: 0.7404
Epoch 23/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0069 - accuracy: 0.9981

264/264 [==============================] - 1s 4ms/step - loss: 0.0069 - accuracy: 0.9981 - val_loss: 2.0778 - val_accuracy: 0.7230
Epoch 24/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0340 - accuracy: 0.9887

264/264 [==============================] - 1s 4ms/step - loss: 0.0340 - accuracy: 0.9887 - val_loss: 1.8337 - val_accuracy: 0.7261
Epoch 25/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0236 - accuracy: 0.9923 - val_loss: 1.8268 - val_accuracy: 0.7322
Epoch 26/30

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264/264 [==============================] - 1s 3ms/step - loss: 0.0056 - accuracy: 0.9984

264/264 [==============================] - 1s 4ms/step - loss: 0.0056 - accuracy: 0.9984 - val_loss: 1.9701 - val_accuracy: 0.7259
Epoch 27/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0029 - accuracy: 0.9994 - val_loss: 1.9856 - val_accuracy: 0.7325
Epoch 28/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0013 - accuracy: 0.9995 - val_loss: 2.0608 - val_accuracy: 0.7329
Epoch 29/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0017 - accuracy: 0.9995 - val_loss: 2.0339 - val_accuracy: 0.7353
Epoch 30/30

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264/264 [==============================] - 1s 4ms/step - loss: 0.0013 - accuracy: 0.9996 - val_loss: 2.0486 - val_accuracy: 0.7350

Run completed: runs/2023-03-31T02-08-59Z

Training run 9/9 (flags = list(64, 0.05, 100, 50, "tanh")) 
Using run directory runs/2023-03-31T02-09-31Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 5000) %>%
+   layer_dense(units = FLAGS$nodes, activatio .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('accuracy .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   covid_train_dtm,covid_train$Sentiment, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(covid_valid_d .... [TRUNCATED] 
Epoch 1/50

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WARNING:tensorflow:Callback method `on_train_batch_end` is slow compared to the batch time (batch time: 0.0026s vs `on_train_batch_end` time: 0.0038s). Check your callbacks.
WARNING:tensorflow:Callback method `on_train_batch_end` is slow compared to the batch time (batch time: 0.0026s vs `on_train_batch_end` time: 0.0038s). Check your callbacks.


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264/264 [==============================] - 2s 6ms/step - loss: 0.7226 - accuracy: 0.6919 - val_loss: 0.6040 - val_accuracy: 0.7572
Epoch 2/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.4410 - accuracy: 0.8357 - val_loss: 0.6060 - val_accuracy: 0.7602
Epoch 3/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.3225 - accuracy: 0.8851 - val_loss: 0.6708 - val_accuracy: 0.7575
Epoch 4/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.2190 - accuracy: 0.9259 - val_loss: 0.7641 - val_accuracy: 0.7510
Epoch 5/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.1302 - accuracy: 0.9604 - val_loss: 0.9292 - val_accuracy: 0.7426
Epoch 6/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0686 - accuracy: 0.9822 - val_loss: 1.1163 - val_accuracy: 0.7355
Epoch 7/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0363 - accuracy: 0.9918 - val_loss: 1.2773 - val_accuracy: 0.7350
Epoch 8/50

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264/264 [==============================] - 1s 3ms/step - loss: 0.0199 - accuracy: 0.9956

264/264 [==============================] - 1s 4ms/step - loss: 0.0199 - accuracy: 0.9956 - val_loss: 1.4052 - val_accuracy: 0.7378
Epoch 9/50

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264/264 [==============================] - 1s 3ms/step - loss: 0.0110 - accuracy: 0.9976 - val_loss: 1.4952 - val_accuracy: 0.7360
Epoch 10/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0073 - accuracy: 0.9986 - val_loss: 1.5812 - val_accuracy: 0.7355
Epoch 11/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0058 - accuracy: 0.9987 - val_loss: 1.6785 - val_accuracy: 0.7378
Epoch 12/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0051 - accuracy: 0.9989 - val_loss: 1.7321 - val_accuracy: 0.7357
Epoch 13/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0042 - accuracy: 0.9989 - val_loss: 1.8703 - val_accuracy: 0.7285
Epoch 14/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0152 - accuracy: 0.9961

264/264 [==============================] - 1s 5ms/step - loss: 0.0152 - accuracy: 0.9961 - val_loss: 1.8956 - val_accuracy: 0.7121
Epoch 15/50

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264/264 [==============================] - 1s 3ms/step - loss: 0.0741 - accuracy: 0.9745

264/264 [==============================] - 1s 4ms/step - loss: 0.0741 - accuracy: 0.9745 - val_loss: 1.6116 - val_accuracy: 0.7243
Epoch 16/50

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264/264 [==============================] - 1s 3ms/step - loss: 0.0315 - accuracy: 0.9899

264/264 [==============================] - 1s 4ms/step - loss: 0.0315 - accuracy: 0.9899 - val_loss: 1.5867 - val_accuracy: 0.7340
Epoch 17/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0078 - accuracy: 0.9981 - val_loss: 1.7599 - val_accuracy: 0.7385
Epoch 18/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0036 - accuracy: 0.9991 - val_loss: 1.8311 - val_accuracy: 0.7381
Epoch 19/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0024 - accuracy: 0.9993 - val_loss: 1.8760 - val_accuracy: 0.7358
Epoch 20/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0023 - accuracy: 0.9993 - val_loss: 1.9225 - val_accuracy: 0.7384
Epoch 21/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0027 - accuracy: 0.9993 - val_loss: 1.9967 - val_accuracy: 0.7396
Epoch 22/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0027 - accuracy: 0.9992 - val_loss: 1.9961 - val_accuracy: 0.7379
Epoch 23/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0026 - accuracy: 0.9992 - val_loss: 2.1080 - val_accuracy: 0.7364
Epoch 24/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0023 - accuracy: 0.9993 - val_loss: 2.0721 - val_accuracy: 0.7341
Epoch 25/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0021 - accuracy: 0.9994 - val_loss: 2.1463 - val_accuracy: 0.7285
Epoch 26/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0067 - accuracy: 0.9982 - val_loss: 2.0160 - val_accuracy: 0.7267
Epoch 27/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0181 - accuracy: 0.9943 - val_loss: 2.0682 - val_accuracy: 0.7206
Epoch 28/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0201 - accuracy: 0.9940 - val_loss: 1.9779 - val_accuracy: 0.7343
Epoch 29/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0096 - accuracy: 0.9970 - val_loss: 2.0489 - val_accuracy: 0.7264
Epoch 30/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0048 - accuracy: 0.9983 - val_loss: 2.0833 - val_accuracy: 0.7288
Epoch 31/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0027 - accuracy: 0.9991 - val_loss: 2.2187 - val_accuracy: 0.7414
Epoch 32/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0035 - accuracy: 0.9990 - val_loss: 2.1957 - val_accuracy: 0.7290
Epoch 33/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0021 - accuracy: 0.9992 - val_loss: 2.2201 - val_accuracy: 0.7287
Epoch 34/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0022 - accuracy: 0.9992 - val_loss: 2.3037 - val_accuracy: 0.7261
Epoch 35/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0026 - accuracy: 0.9993 - val_loss: 2.2992 - val_accuracy: 0.7325
Epoch 36/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0017 - accuracy: 0.9994 - val_loss: 2.3466 - val_accuracy: 0.7385
Epoch 37/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0020 - accuracy: 0.9994 - val_loss: 2.3473 - val_accuracy: 0.7350
Epoch 38/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0032 - accuracy: 0.9989 - val_loss: 2.3509 - val_accuracy: 0.7329
Epoch 39/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0034 - accuracy: 0.9990 - val_loss: 2.3981 - val_accuracy: 0.7275
Epoch 40/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0130 - accuracy: 0.9954 - val_loss: 2.3233 - val_accuracy: 0.7258
Epoch 41/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0107 - accuracy: 0.9965 - val_loss: 2.2752 - val_accuracy: 0.7189
Epoch 42/50

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Epoch 43/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0030 - accuracy: 0.9992 - val_loss: 2.2574 - val_accuracy: 0.7322
Epoch 44/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0016 - accuracy: 0.9994 - val_loss: 2.3083 - val_accuracy: 0.7256
Epoch 45/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0021 - accuracy: 0.9994 - val_loss: 2.3112 - val_accuracy: 0.7300
Epoch 46/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0016 - accuracy: 0.9994 - val_loss: 2.3904 - val_accuracy: 0.7268
Epoch 47/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0025 - accuracy: 0.9993 - val_loss: 2.3022 - val_accuracy: 0.7343
Epoch 48/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0027 - accuracy: 0.9994 - val_loss: 2.3157 - val_accuracy: 0.7303
Epoch 49/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0015 - accuracy: 0.9995 - val_loss: 2.3432 - val_accuracy: 0.7252
Epoch 50/50

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264/264 [==============================] - 1s 4ms/step - loss: 0.0019 - accuracy: 0.9993 - val_loss: 2.4576 - val_accuracy: 0.7276

Run completed: runs/2023-03-31T02-09-31Z

runs

Data frame: 9 x 25 

# ... with 20 more columns:
#   flag_nodes, flag_batch_size, flag_activation, flag_learning_rate, flag_epochs, epochs, epochs_completed, metrics, model, loss_function, optimizer, learning_rate, script, start, end, completed,
#   output, source_code, context, type

runs

Data frame: 9 x 25 

# ... with 20 more columns:
#   flag_nodes, flag_batch_size, flag_activation, flag_learning_rate, flag_epochs, epochs, epochs_completed, metrics, model,
#   loss_function, optimizer, learning_rate, script, start, end, completed, output, source_code, context, type

view_run(runs$run_dir[2])

Warning: argument 'compressed' is ignored for the internal methodWarning: incomplete final line found on 'C:\Users\JERRYP~1\AppData\Local\Temp\Rtmpyotyha\file6af87b456ffe/source/Corona_NLP_train.R'Warning: incomplete final line found on 'C:\Users\JERRYP~1\AppData\Local\Temp\Rtmpyotyha\file6af87b456ffe/source/fashion_mnist.R'

1. Run number 2 with a validation accuracy of 73.5% was the model that resulted in the best accuracy on the validation data.

2. The best model overfits by a lot because the validation error is much higher than the training error.

3. The validation_loss seems to be steadily increasing and then decreases at around 24 epochs before steadily increasing again.

Q3. Add the validation data to the train data.

covid_train_dtm_matrix <- as.matrix(covid_train_dtm)
covid_valid_dtm_matrix <- as.matrix(covid_valid_dtm)

covid_matrix <- rbind(covid_train_dtm_matrix, covid_valid_dtm_matrix)
covid_combined <- rbind(covid_train, covid_valid)

model = keras_model_sequential()

model %>%
  layer_dense(units = 64, activation = "tanh", input_shape = 5000) %>%
  layer_dense(units = 64, activation = "tanh") %>%
  layer_dense(units = 3, activation = "softmax")

model %>% compile(
  optimizer = optimizer_adam(lr = 0.01),
  loss = 'sparse_categorical_crossentropy',
  metrics = c('accuracy')
)

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

model %>% fit(
  covid_matrix,covid_combined$Sentiment, epochs = 30, batch_size = 100, validation_data = list(covid_valid_dtm,covid_valid$Sentiment)
)

Epoch 1/30

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330/330 [==============================] - 2s 4ms/step - loss: 0.7002 - accuracy: 0.6981

330/330 [==============================] - 3s 7ms/step - loss: 0.7002 - accuracy: 0.6981 - val_loss: 0.4205 - val_accuracy: 0.8521
Epoch 2/30

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330/330 [==============================] - 1s 4ms/step - loss: 0.4422 - accuracy: 0.8346

330/330 [==============================] - 2s 5ms/step - loss: 0.4422 - accuracy: 0.8346 - val_loss: 0.3259 - val_accuracy: 0.8930
Epoch 3/30

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330/330 [==============================] - 1s 4ms/step - loss: 0.3324 - accuracy: 0.8777

330/330 [==============================] - 1s 5ms/step - loss: 0.3324 - accuracy: 0.8777 - val_loss: 0.2212 - val_accuracy: 0.9329
Epoch 4/30

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330/330 [==============================] - 1s 4ms/step - loss: 0.2305 - accuracy: 0.9190

330/330 [==============================] - 2s 5ms/step - loss: 0.2305 - accuracy: 0.9190 - val_loss: 0.1420 - val_accuracy: 0.9607
Epoch 5/30

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330/330 [==============================] - 1s 4ms/step - loss: 0.1388 - accuracy: 0.9548

330/330 [==============================] - 1s 5ms/step - loss: 0.1388 - accuracy: 0.9548 - val_loss: 0.0755 - val_accuracy: 0.9824
Epoch 6/30

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330/330 [==============================] - 1s 4ms/step - loss: 0.0724 - accuracy: 0.9799

330/330 [==============================] - 1s 4ms/step - loss: 0.0724 - accuracy: 0.9799 - val_loss: 0.0373 - val_accuracy: 0.9929
Epoch 7/30

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330/330 [==============================] - 1s 5ms/step - loss: 0.0377 - accuracy: 0.9913 - val_loss: 0.0191 - val_accuracy: 0.9970
Epoch 8/30

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330/330 [==============================] - 1s 4ms/step - loss: 0.0188 - accuracy: 0.9961

330/330 [==============================] - 2s 5ms/step - loss: 0.0188 - accuracy: 0.9961 - val_loss: 0.0132 - val_accuracy: 0.9976
Epoch 9/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0116 - accuracy: 0.9976 - val_loss: 0.0076 - val_accuracy: 0.9989
Epoch 10/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0102 - accuracy: 0.9981 - val_loss: 0.0053 - val_accuracy: 0.9992
Epoch 11/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0069 - accuracy: 0.9984 - val_loss: 0.0037 - val_accuracy: 0.9995
Epoch 12/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0066 - accuracy: 0.9984 - val_loss: 0.0083 - val_accuracy: 0.9982
Epoch 13/30

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330/330 [==============================] - 1s 4ms/step - loss: 0.0110 - accuracy: 0.9971

330/330 [==============================] - 2s 5ms/step - loss: 0.0110 - accuracy: 0.9971 - val_loss: 0.0174 - val_accuracy: 0.9967
Epoch 14/30

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330/330 [==============================] - 1s 4ms/step - loss: 0.0520 - accuracy: 0.9829

330/330 [==============================] - 2s 5ms/step - loss: 0.0520 - accuracy: 0.9829 - val_loss: 0.0300 - val_accuracy: 0.9897
Epoch 15/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0297 - accuracy: 0.9903 - val_loss: 0.0141 - val_accuracy: 0.9959
Epoch 16/30

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330/330 [==============================] - 1s 4ms/step - loss: 0.0112 - accuracy: 0.9968

330/330 [==============================] - 2s 5ms/step - loss: 0.0112 - accuracy: 0.9968 - val_loss: 0.0051 - val_accuracy: 0.9992
Epoch 17/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0053 - accuracy: 0.9988 - val_loss: 0.0014 - val_accuracy: 1.0000
Epoch 18/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0022 - accuracy: 0.9994 - val_loss: 0.0012 - val_accuracy: 0.9995
Epoch 19/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0019 - accuracy: 0.9995 - val_loss: 0.0021 - val_accuracy: 0.9998
Epoch 20/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0021 - accuracy: 0.9993 - val_loss: 9.0462e-04 - val_accuracy: 0.9998
Epoch 21/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0019 - accuracy: 0.9994 - val_loss: 6.3120e-04 - val_accuracy: 1.0000
Epoch 22/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0020 - accuracy: 0.9995 - val_loss: 7.8623e-04 - val_accuracy: 0.9998
Epoch 23/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0031 - accuracy: 0.9991 - val_loss: 0.0031 - val_accuracy: 0.9992
Epoch 24/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0053 - accuracy: 0.9985 - val_loss: 0.0038 - val_accuracy: 0.9992
Epoch 25/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0223 - accuracy: 0.9926 - val_loss: 0.0175 - val_accuracy: 0.9947
Epoch 26/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0179 - accuracy: 0.9938 - val_loss: 0.0109 - val_accuracy: 0.9967
Epoch 27/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0114 - accuracy: 0.9967 - val_loss: 0.0037 - val_accuracy: 0.9985
Epoch 28/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0033 - accuracy: 0.9989 - val_loss: 0.0011 - val_accuracy: 0.9995
Epoch 29/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0021 - accuracy: 0.9993 - val_loss: 0.0017 - val_accuracy: 0.9995
Epoch 30/30

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330/330 [==============================] - 2s 5ms/step - loss: 0.0016 - accuracy: 0.9995 - val_loss: 0.0013 - val_accuracy: 0.9995

new_pred_labels = as.numeric(model %>% predict(covid_test_dtm) %>% k_argmax())

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CrossTable(new_pred_labels,covid_test$Sentiment, prop.chisq = FALSE, prop.t = FALSE, dnn = c('predicted','actual'))

 
   Cell Contents
|-------------------------|
|                       N |
|           N / Row Total |
|           N / Col Total |
|-------------------------|

 
Total Observations in Table:  8232 

 
             | actual 
   predicted |         0 |         1 |         2 | Row Total | 
-------------|-----------|-----------|-----------|-----------|
           0 |      2232 |       409 |       257 |      2898 | 
             |     0.770 |     0.141 |     0.089 |     0.352 | 
             |     0.724 |     0.114 |     0.165 |           | 
-------------|-----------|-----------|-----------|-----------|
           1 |       594 |      2982 |       377 |      3953 | 
             |     0.150 |     0.754 |     0.095 |     0.480 | 
             |     0.193 |     0.829 |     0.242 |           | 
-------------|-----------|-----------|-----------|-----------|
           2 |       255 |       204 |       922 |      1381 | 
             |     0.185 |     0.148 |     0.668 |     0.168 | 
             |     0.083 |     0.057 |     0.593 |           | 
-------------|-----------|-----------|-----------|-----------|
Column Total |      3081 |      3595 |      1556 |      8232 | 
             |     0.374 |     0.437 |     0.189 |           | 
-------------|-----------|-----------|-----------|-----------|

 

Best model from this assignment:

Overall accuracy would be 6136/ 8232 = .745.

Precision = TP/(TP+FP) recall= TP/(TP+FN)

Negative : Precision = 2232/ (2232 + 409 + 257) = .77 , Recall = 2232 / (2232 + 594 + 255) = .724

Positive : Precision = 2982 / (2982 + 594 + 377) = .754 , Recall = 2982 / (2982 + 409 + 204 )= .829

Neutral : Precision = 922 / (922 + 255 + 204) = .667 , Recall = 922 / (922 + 257 + 377) = .592

Naive Bayes model from Assignment 2:

Overall accuracy would be 5683/ 8232 = 69%.

Precision = TP/(TP+FP) recall= TP/(TP+FN)

Negative : Recall = 2044/ (2044 + 627 + 410) = .663 , Precision = 2044 / (2044 +607 + 214) = .713

Positive : Recall = 2576 / (2576 + 607 + 412) = .717 , Precision = 2576 / (2576 + 627 + 279 )= .740

Neutral : Recall = 1063 / (1063 + 214 + 279) = .683 , Precision = 1063 / (1063 + 410 + 412) = .564

This model has a higher accuracy value than the naive Bayes model from the previous assignment with .745 vs .69. This model performed better than the naive Bayes model in both precision and recall.

Problem 2

1. Explore the overall structure of the dataset using str() function. Get a summary of statistics from each variable

bike <- read.csv("bike.csv")
str(bike)
summary(bike)

There are 10886 observations in the data.

datetime: Categorical, ordinal variable

season: Categorical, ordinal variable

holiday: Categorical, nominal variable

workingday: Categorical, nominal variable

weather: Categorical, ordinal variable

temp: Continuous variable

atemp: Continious variable

humidity: Continuous variable

windspeed: Continuous variable

registered: Continuous variable

count: Continous variable

colSums(is.na(bike))

There appear to be no missing values in the dataset.

hist(bike$count)

The histogram’s shape is reverse J-shaped, and it has a right-skewed distribution.

2. Remove registered and casual variables.

new_bike <- subset(bike, select = -c(registered,casual))

3. Set count variable in the dataframe equal to square root of count and plot the distribution.

new_bike$count <- sqrt(new_bike$count)

hist(new_bike$count)

4. Convert datetime to “day of month”, “year”, “day of week”, “month”, and “hour” variables.

library(lubridate)
new_bike$datetime <- as.POSIXlt(new_bike$datetime)
dayofmonth = new_bike$datetime$mday
year = new_bike$datetime$year
dayofweek = new_bike$datetime$wday
month = new_bike$datetime$mon
hour = new_bike$datetime$hour

new_bike <- cbind(new_bike, dayofmonth,year,dayofweek,month,hour)

new_bike <- subset(new_bike, select = -datetime)

5. Convert variables month, day of week, hour, and season to their x and y coordinates using sin and cosine transformation. After transformation, make sure to remove the original variables.

month_x <- cos(((2*pi) * new_bike$month) / max(new_bike$month))

Warning: no non-missing arguments to max; returning -Inf

month_y <- sin(((2*pi) * new_bike$month)/ max(new_bike$month))

Warning: no non-missing arguments to max; returning -Inf

dayofweek_x <- cos(((2*pi) * new_bike$dayofweek) / max(new_bike$dayofweek))

Warning: no non-missing arguments to max; returning -Inf

dayofweek_y <- sin(((2*pi) * new_bike$dayofweek) / max(new_bike$dayofweek))

Warning: no non-missing arguments to max; returning -Inf

hour_x <- cos(((2*pi) * new_bike$hour) / max(new_bike$hour))

Warning: no non-missing arguments to max; returning -Inf

hour_y <- sin(((2*pi) * new_bike$hour)/ max(new_bike$hour))

Warning: no non-missing arguments to max; returning -Inf

season_x <- cos(((2*pi) * new_bike$season) / max(new_bike$season))

Warning: no non-missing arguments to max; returning -Inf

season_y <- sin(((2*pi) * new_bike$season)/ max(new_bike$season))

Warning: no non-missing arguments to max; returning -Inf

new_bike$dayofmonth <- as.numeric(new_bike$dayofmonth)

new_bike <- cbind(new_bike, month_x,month_y, dayofweek_x,dayofweek_y,hour_x,hour_y,season_x,season_y)

new_bike <- subset(new_bike, select = -c(month,dayofweek,hour,season))

library(data.table)
library(mltools)
new_bike_dt <- as.data.table(new_bike)
new_bike_dt$season_x <- factor(new_bike_dt$season_x)
new_bike_dt$season_y <- factor(new_bike_dt$season_y)
new_bike_dt$month_x <- factor(new_bike_dt$month_x)
new_bike_dt$month_y <- factor(new_bike_dt$month_y)
new_bike_dt$dayofweek_x <- factor(new_bike_dt$dayofweek_x)
new_bike_dt$dayofweek_y <- factor(new_bike_dt$dayofweek_y)
new_bike_dt$hour_x <- factor(new_bike_dt$hour_x)
new_bike_dt$hour_y <- factor(new_bike_dt$hour_y)
new_bike_dt$dayofmonth <- factor(new_bike_dt$dayofmonth)
new_bike_dt$weather <- factor(new_bike_dt$weather)
new_bike_dt$year <- factor(new_bike_dt$year)

new_bike_hot <-one_hot(new_bike_dt, cols = c("season_x","season_y", "month_x", "month_y", "dayofmonth", "year","dayofweek_x","dayofweek_y", "hour_x","hour_y", "weather"), sparsifyNAs = FALSE, naCols =FALSE, dropCols =TRUE, dropUnusedLevels = TRUE)

7. Use set.seed(1) to set random seed

set.seed(1)

8. Use Caret’s createDataPartition method as follows to partition dataset into bikes_train and bikes_test (90% training and 10% testing)

library(caret)
inTrain = createDataPartition(new_bike_hot$count, p = 0.9, list = FALSE)
bikes_train = new_bike_hot[inTrain,]
new_bikes_test = new_bike_hot[-inTrain,]

9. Set seed and further divide the train dat into 90% training and 10% validation

set.seed(1)

second_bikes_train <- createDataPartition(bikes_train$count, p = .90, list = FALSE)

second_bikes_train_set <- bikes_train[second_bikes_train,]
second_bikes_valid <- bikes_train[-second_bikes_train,]

10. Scale the numeric attributes in the training data (except for the outcome variable, count). Use the column means and column stdev from the training data to scale both validation and test data. Do NOT scale dummy variables (Season, month, dayofmonth, hour, year, dayofweek, weather)

numeric_cols = c("temp", "atemp", "humidity", "windspeed")

second_bikes_train_set <- as.data.frame(second_bikes_train_set)
new_bikes_test <- as.data.frame(new_bikes_test)
second_bikes_valid <- as.data.frame(second_bikes_valid)

col_means_train <- attr(scale(second_bikes_train_set[,numeric_cols]), "scaled:center")
col_stddevs_train <- attr(scale(second_bikes_train_set[, numeric_cols]), "scaled:scale")


second_bikes_train_set[numeric_cols] = scale(second_bikes_train_set[numeric_cols])
new_bikes_test[numeric_cols] <- scale(second_bikes_train_set[numeric_cols], center = col_means_train, scale = col_stddevs_train)

Warning: data length [35280] is not a sub-multiple or multiple of the number of rows [1087]

second_bikes_valid[numeric_cols] <- scale(second_bikes_train_set[numeric_cols], center = col_means_train, scale = col_stddevs_train)

Warning: data length [35280] is not a sub-multiple or multiple of the number of rows [979]

11. Create an ANN to predict count from other attributes. Use at least 2 hidden layers. Use tfruns to tune hyper-parameters (number of nodes in each hidden layer, activation function in each hidden layer, batch_size, learning_rate, and number of epochs). Validate each moidel on the validation set.

second_bikes_matrix <- as.matrix(second_bikes_train_set)
second_bikes_valid_matrix <- as.matrix(second_bikes_valid)

bike_model = keras_model_sequential()

bike_model %>%
  layer_dense(units = 1000, activation = "relu", input_shape = 106)%>%
  layer_dense(units = 400, activation = "relu",) %>%
  layer_dense(units = 106, activation = "softmax")


bike_model %>% compile(
  optimizer = 'adam',
  loss = 'sparse_categorical_crossentropy',
  metrics = c('mse')
)
set.seed(1)

bike_model %>% fit(
  second_bikes_matrix, second_bikes_train_set$count, epochs = 30, batch_size = 100, validation_data = list(as.matrix(second_bikes_valid_matrix), second_bikes_valid$count)
)

Epoch 1/30

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89/89 [==============================] - 2s 16ms/step - loss: 2.4243 - mse: 191.6126 - val_loss: 1.7762 - val_mse: 188.1762
Epoch 2/30

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89/89 [==============================] - 1s 11ms/step - loss: 1.4463 - mse: 191.6140 - val_loss: 1.2811 - val_mse: 188.1774
Epoch 3/30

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89/89 [==============================] - 1s 11ms/step - loss: 1.0713 - mse: 191.6149 - val_loss: 1.0471 - val_mse: 188.1781
Epoch 4/30

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89/89 [==============================] - 1s 11ms/step - loss: 0.8804 - mse: 191.6157 - val_loss: 0.8385 - val_mse: 188.1787
Epoch 5/30

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89/89 [==============================] - 1s 11ms/step - loss: 0.7250 - mse: 191.6162 - val_loss: 0.7860 - val_mse: 188.1793
Epoch 6/30

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89/89 [==============================] - 1s 10ms/step - loss: 0.6252 - mse: 191.6167 - val_loss: 0.8705 - val_mse: 188.1799
Epoch 7/30

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89/89 [==============================] - 1s 9ms/step - loss: 0.5749 - mse: 191.6170

89/89 [==============================] - 1s 11ms/step - loss: 0.5749 - mse: 191.6170 - val_loss: 0.7027 - val_mse: 188.1801
Epoch 8/30

 1/89 [..............................] - ETA: 0s - loss: 0.5456 - mse: 192.7023
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89/89 [==============================] - 1s 9ms/step - loss: 0.5341 - mse: 191.6174

89/89 [==============================] - 1s 11ms/step - loss: 0.5341 - mse: 191.6174 - val_loss: 0.6483 - val_mse: 188.1801
Epoch 9/30

 1/89 [..............................] - ETA: 0s - loss: 0.4748 - mse: 202.1682
 7/89 [=>............................] - ETA: 0s - loss: 0.5509 - mse: 203.7152
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89/89 [==============================] - 1s 9ms/step - loss: 0.4836 - mse: 191.6176

89/89 [==============================] - 1s 11ms/step - loss: 0.4836 - mse: 191.6176 - val_loss: 0.5704 - val_mse: 188.1804
Epoch 10/30

 1/89 [..............................] - ETA: 0s - loss: 0.3853 - mse: 170.9081
 7/89 [=>............................] - ETA: 0s - loss: 0.4214 - mse: 174.1746
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89/89 [==============================] - 1s 9ms/step - loss: 0.4280 - mse: 191.6179

89/89 [==============================] - 1s 11ms/step - loss: 0.4280 - mse: 191.6179 - val_loss: 0.5606 - val_mse: 188.1805
Epoch 11/30

 1/89 [..............................] - ETA: 0s - loss: 0.4212 - mse: 200.9294
 7/89 [=>............................] - ETA: 0s - loss: 0.5458 - mse: 195.0892
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89/89 [==============================] - 1s 9ms/step - loss: 0.4388 - mse: 191.6180

89/89 [==============================] - 1s 11ms/step - loss: 0.4388 - mse: 191.6180 - val_loss: 0.5284 - val_mse: 188.1808
Epoch 12/30

 1/89 [..............................] - ETA: 0s - loss: 0.4257 - mse: 202.0247
 7/89 [=>............................] - ETA: 0s - loss: 0.3846 - mse: 187.4765
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89/89 [==============================] - 1s 9ms/step - loss: 0.3764 - mse: 191.6183

89/89 [==============================] - 1s 11ms/step - loss: 0.3764 - mse: 191.6183 - val_loss: 0.5017 - val_mse: 188.1808
Epoch 13/30

 1/89 [..............................] - ETA: 0s - loss: 0.2495 - mse: 186.1568
 7/89 [=>............................] - ETA: 0s - loss: 0.3637 - mse: 193.8854
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89/89 [==============================] - 1s 9ms/step - loss: 0.3208 - mse: 191.6184

89/89 [==============================] - 1s 11ms/step - loss: 0.3208 - mse: 191.6184 - val_loss: 0.5855 - val_mse: 188.1810
Epoch 14/30

 1/89 [..............................] - ETA: 0s - loss: 0.2187 - mse: 159.9124
 7/89 [=>............................] - ETA: 0s - loss: 0.3450 - mse: 183.7856
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89/89 [==============================] - 1s 9ms/step - loss: 0.3235 - mse: 191.6186

89/89 [==============================] - 1s 11ms/step - loss: 0.3235 - mse: 191.6186 - val_loss: 0.6977 - val_mse: 188.1811
Epoch 15/30

 1/89 [..............................] - ETA: 0s - loss: 0.2928 - mse: 191.7928
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89/89 [==============================] - 1s 9ms/step - loss: 0.3096 - mse: 191.6187

89/89 [==============================] - 1s 11ms/step - loss: 0.3096 - mse: 191.6187 - val_loss: 0.4300 - val_mse: 188.1812
Epoch 16/30

 1/89 [..............................] - ETA: 0s - loss: 0.3033 - mse: 183.7023
 7/89 [=>............................] - ETA: 0s - loss: 0.3059 - mse: 206.3242
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89/89 [==============================] - 1s 9ms/step - loss: 0.2914 - mse: 191.6187

89/89 [==============================] - 1s 11ms/step - loss: 0.2914 - mse: 191.6187 - val_loss: 0.4470 - val_mse: 188.1813
Epoch 17/30

 1/89 [..............................] - ETA: 0s - loss: 0.2802 - mse: 203.5307
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89/89 [==============================] - 1s 9ms/step - loss: 0.2816 - mse: 191.6189

89/89 [==============================] - 1s 11ms/step - loss: 0.2816 - mse: 191.6189 - val_loss: 0.6037 - val_mse: 188.1813
Epoch 18/30

 1/89 [..............................] - ETA: 0s - loss: 0.1745 - mse: 166.3838
 7/89 [=>............................] - ETA: 0s - loss: 0.2961 - mse: 193.8636
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89/89 [==============================] - 1s 9ms/step - loss: 0.2455 - mse: 191.6190

89/89 [==============================] - 1s 11ms/step - loss: 0.2455 - mse: 191.6190 - val_loss: 0.4457 - val_mse: 188.1814
Epoch 19/30

 1/89 [..............................] - ETA: 0s - loss: 0.1906 - mse: 200.6945
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89/89 [==============================] - 1s 9ms/step - loss: 0.2262 - mse: 191.6191

89/89 [==============================] - 1s 11ms/step - loss: 0.2262 - mse: 191.6191 - val_loss: 0.6389 - val_mse: 188.1816
Epoch 20/30

 1/89 [..............................] - ETA: 0s - loss: 0.2153 - mse: 211.1071
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89/89 [==============================] - 1s 9ms/step - loss: 0.2546 - mse: 191.6191

89/89 [==============================] - 1s 11ms/step - loss: 0.2546 - mse: 191.6191 - val_loss: 0.7127 - val_mse: 188.1817
Epoch 21/30

 1/89 [..............................] - ETA: 0s - loss: 0.1783 - mse: 164.4214
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89/89 [==============================] - 1s 9ms/step - loss: 0.2163 - mse: 191.6193

89/89 [==============================] - 1s 11ms/step - loss: 0.2163 - mse: 191.6193 - val_loss: 0.5404 - val_mse: 188.1816
Epoch 22/30

 1/89 [..............................] - ETA: 0s - loss: 0.2338 - mse: 234.7081
 7/89 [=>............................] - ETA: 0s - loss: 0.2511 - mse: 207.3219
13/89 [===>..........................] - ETA: 0s - loss: 0.2387 - mse: 191.0954
19/89 [=====>........................] - ETA: 0s - loss: 0.2411 - mse: 192.1563
25/89 [=======>......................] - ETA: 0s - loss: 0.2281 - mse: 191.6137
31/89 [=========>....................] - ETA: 0s - loss: 0.2281 - mse: 192.5488
37/89 [===========>..................] - ETA: 0s - loss: 0.2188 - mse: 191.7705
43/89 [=============>................] - ETA: 0s - loss: 0.2123 - mse: 190.5523
49/89 [===============>..............] - ETA: 0s - loss: 0.2109 - mse: 191.0456
55/89 [=================>............] - ETA: 0s - loss: 0.2092 - mse: 191.4306
61/89 [===================>..........] - ETA: 0s - loss: 0.2099 - mse: 191.4489
67/89 [=====================>........] - ETA: 0s - loss: 0.2119 - mse: 190.9542
73/89 [=======================>......] - ETA: 0s - loss: 0.2142 - mse: 192.3661
79/89 [=========================>....] - ETA: 0s - loss: 0.2165 - mse: 191.7036
85/89 [===========================>..] - ETA: 0s - loss: 0.2193 - mse: 191.8086
89/89 [==============================] - 1s 9ms/step - loss: 0.2197 - mse: 191.6192

89/89 [==============================] - 1s 11ms/step - loss: 0.2197 - mse: 191.6192 - val_loss: 0.5123 - val_mse: 188.1816
Epoch 23/30

 1/89 [..............................] - ETA: 0s - loss: 0.1938 - mse: 220.5032
 7/89 [=>............................] - ETA: 0s - loss: 0.2716 - mse: 200.1539
13/89 [===>..........................] - ETA: 0s - loss: 0.2679 - mse: 196.8308
19/89 [=====>........................] - ETA: 0s - loss: 0.2604 - mse: 195.1381
25/89 [=======>......................] - ETA: 0s - loss: 0.2473 - mse: 193.3650
31/89 [=========>....................] - ETA: 0s - loss: 0.2371 - mse: 192.8819
37/89 [===========>..................] - ETA: 0s - loss: 0.2309 - mse: 193.5923
43/89 [=============>................] - ETA: 0s - loss: 0.2289 - mse: 196.1910
49/89 [===============>..............] - ETA: 0s - loss: 0.2245 - mse: 195.8695
55/89 [=================>............] - ETA: 0s - loss: 0.2235 - mse: 195.7119
61/89 [===================>..........] - ETA: 0s - loss: 0.2227 - mse: 194.1911
67/89 [=====================>........] - ETA: 0s - loss: 0.2188 - mse: 193.1904
73/89 [=======================>......] - ETA: 0s - loss: 0.2154 - mse: 192.8038
79/89 [=========================>....] - ETA: 0s - loss: 0.2117 - mse: 192.3023
85/89 [===========================>..] - ETA: 0s - loss: 0.2091 - mse: 191.7552
89/89 [==============================] - 1s 9ms/step - loss: 0.2070 - mse: 191.6194

89/89 [==============================] - 1s 10ms/step - loss: 0.2070 - mse: 191.6194 - val_loss: 0.5847 - val_mse: 188.1818
Epoch 24/30

 1/89 [..............................] - ETA: 0s - loss: 0.1585 - mse: 209.0944
 7/89 [=>............................] - ETA: 0s - loss: 0.1931 - mse: 197.8240
13/89 [===>..........................] - ETA: 0s - loss: 0.1990 - mse: 198.5456
19/89 [=====>........................] - ETA: 0s - loss: 0.1884 - mse: 199.3055
25/89 [=======>......................] - ETA: 0s - loss: 0.1861 - mse: 197.8087
31/89 [=========>....................] - ETA: 0s - loss: 0.1844 - mse: 196.5601
37/89 [===========>..................] - ETA: 0s - loss: 0.1810 - mse: 194.8438
43/89 [=============>................] - ETA: 0s - loss: 0.1844 - mse: 193.9919
49/89 [===============>..............] - ETA: 0s - loss: 0.1882 - mse: 192.5598
55/89 [=================>............] - ETA: 0s - loss: 0.1876 - mse: 192.8454
61/89 [===================>..........] - ETA: 0s - loss: 0.1863 - mse: 191.5850
67/89 [=====================>........] - ETA: 0s - loss: 0.1893 - mse: 191.9673
73/89 [=======================>......] - ETA: 0s - loss: 0.1903 - mse: 191.5159
79/89 [=========================>....] - ETA: 0s - loss: 0.1908 - mse: 191.5229
85/89 [===========================>..] - ETA: 0s - loss: 0.1887 - mse: 191.8515
89/89 [==============================] - 1s 9ms/step - loss: 0.1891 - mse: 191.6195

89/89 [==============================] - 1s 11ms/step - loss: 0.1891 - mse: 191.6195 - val_loss: 0.5882 - val_mse: 188.1817
Epoch 25/30

 1/89 [..............................] - ETA: 0s - loss: 0.1275 - mse: 166.8750
 7/89 [=>............................] - ETA: 0s - loss: 0.2073 - mse: 185.1314
13/89 [===>..........................] - ETA: 0s - loss: 0.1946 - mse: 190.2984
18/89 [=====>........................] - ETA: 0s - loss: 0.1878 - mse: 188.8165
24/89 [=======>......................] - ETA: 0s - loss: 0.1847 - mse: 189.4098
30/89 [=========>....................] - ETA: 0s - loss: 0.1811 - mse: 188.4564
36/89 [===========>..................] - ETA: 0s - loss: 0.1824 - mse: 190.7185
42/89 [=============>................] - ETA: 0s - loss: 0.1797 - mse: 190.2628
48/89 [===============>..............] - ETA: 0s - loss: 0.1778 - mse: 191.5102
54/89 [=================>............] - ETA: 0s - loss: 0.1771 - mse: 191.8434
60/89 [===================>..........] - ETA: 0s - loss: 0.1771 - mse: 192.6210
66/89 [=====================>........] - ETA: 0s - loss: 0.1816 - mse: 192.0531
72/89 [=======================>......] - ETA: 0s - loss: 0.1828 - mse: 191.7965
78/89 [=========================>....] - ETA: 0s - loss: 0.1847 - mse: 191.8242
84/89 [===========================>..] - ETA: 0s - loss: 0.1866 - mse: 191.8282
89/89 [==============================] - 1s 9ms/step - loss: 0.1897 - mse: 191.6194

89/89 [==============================] - 1s 11ms/step - loss: 0.1897 - mse: 191.6194 - val_loss: 0.7489 - val_mse: 188.1818
Epoch 26/30

 1/89 [..............................] - ETA: 0s - loss: 0.2311 - mse: 174.4816
 7/89 [=>............................] - ETA: 0s - loss: 0.2557 - mse: 187.5201
13/89 [===>..........................] - ETA: 0s - loss: 0.2565 - mse: 190.2005
19/89 [=====>........................] - ETA: 0s - loss: 0.2470 - mse: 188.6766
25/89 [=======>......................] - ETA: 0s - loss: 0.2359 - mse: 188.3604
30/89 [=========>....................] - ETA: 0s - loss: 0.2332 - mse: 188.7896
36/89 [===========>..................] - ETA: 0s - loss: 0.2320 - mse: 192.1875
42/89 [=============>................] - ETA: 0s - loss: 0.2250 - mse: 192.5597
48/89 [===============>..............] - ETA: 0s - loss: 0.2185 - mse: 192.4258
54/89 [=================>............] - ETA: 0s - loss: 0.2095 - mse: 191.0367
60/89 [===================>..........] - ETA: 0s - loss: 0.2047 - mse: 191.5254
66/89 [=====================>........] - ETA: 0s - loss: 0.1977 - mse: 190.4542
72/89 [=======================>......] - ETA: 0s - loss: 0.1947 - mse: 191.8323
78/89 [=========================>....] - ETA: 0s - loss: 0.1903 - mse: 191.9318
84/89 [===========================>..] - ETA: 0s - loss: 0.1871 - mse: 192.0630
89/89 [==============================] - 1s 9ms/step - loss: 0.1862 - mse: 191.6195

89/89 [==============================] - 1s 11ms/step - loss: 0.1862 - mse: 191.6195 - val_loss: 0.5994 - val_mse: 188.1818
Epoch 27/30

 1/89 [..............................] - ETA: 0s - loss: 0.0954 - mse: 194.2035
 7/89 [=>............................] - ETA: 0s - loss: 0.2507 - mse: 192.0665
13/89 [===>..........................] - ETA: 0s - loss: 0.2433 - mse: 191.5378
19/89 [=====>........................] - ETA: 0s - loss: 0.2390 - mse: 189.6363
25/89 [=======>......................] - ETA: 0s - loss: 0.2338 - mse: 192.9622
31/89 [=========>....................] - ETA: 0s - loss: 0.2314 - mse: 192.0370
37/89 [===========>..................] - ETA: 0s - loss: 0.2357 - mse: 191.8277
43/89 [=============>................] - ETA: 0s - loss: 0.2349 - mse: 190.4485
49/89 [===============>..............] - ETA: 0s - loss: 0.2335 - mse: 190.8989
55/89 [=================>............] - ETA: 0s - loss: 0.2331 - mse: 190.9428
61/89 [===================>..........] - ETA: 0s - loss: 0.2331 - mse: 190.8778
67/89 [=====================>........] - ETA: 0s - loss: 0.2284 - mse: 190.1814
73/89 [=======================>......] - ETA: 0s - loss: 0.2280 - mse: 190.6928
79/89 [=========================>....] - ETA: 0s - loss: 0.2298 - mse: 191.6922
85/89 [===========================>..] - ETA: 0s - loss: 0.2284 - mse: 191.8936
89/89 [==============================] - 1s 9ms/step - loss: 0.2271 - mse: 191.6195

89/89 [==============================] - 1s 11ms/step - loss: 0.2271 - mse: 191.6195 - val_loss: 0.4763 - val_mse: 188.1818
Epoch 28/30

 1/89 [..............................] - ETA: 0s - loss: 0.2096 - mse: 205.5483
 7/89 [=>............................] - ETA: 0s - loss: 0.2103 - mse: 208.5558
13/89 [===>..........................] - ETA: 0s - loss: 0.2167 - mse: 201.7321
19/89 [=====>........................] - ETA: 0s - loss: 0.2119 - mse: 196.8536
25/89 [=======>......................] - ETA: 0s - loss: 0.2092 - mse: 197.9748
31/89 [=========>....................] - ETA: 0s - loss: 0.1994 - mse: 195.8729
37/89 [===========>..................] - ETA: 0s - loss: 0.1968 - mse: 194.5120
43/89 [=============>................] - ETA: 0s - loss: 0.1921 - mse: 193.7974
49/89 [===============>..............] - ETA: 0s - loss: 0.1912 - mse: 192.6672
55/89 [=================>............] - ETA: 0s - loss: 0.1875 - mse: 193.1293
61/89 [===================>..........] - ETA: 0s - loss: 0.1859 - mse: 192.9574
67/89 [=====================>........] - ETA: 0s - loss: 0.1853 - mse: 193.0844
73/89 [=======================>......] - ETA: 0s - loss: 0.1823 - mse: 191.9385
79/89 [=========================>....] - ETA: 0s - loss: 0.1814 - mse: 191.6418
85/89 [===========================>..] - ETA: 0s - loss: 0.1817 - mse: 191.7488
89/89 [==============================] - 1s 9ms/step - loss: 0.1801 - mse: 191.6195

89/89 [==============================] - 1s 11ms/step - loss: 0.1801 - mse: 191.6195 - val_loss: 0.4905 - val_mse: 188.1819
Epoch 29/30

 1/89 [..............................] - ETA: 0s - loss: 0.0991 - mse: 172.6263
 7/89 [=>............................] - ETA: 0s - loss: 0.2088 - mse: 185.6263
13/89 [===>..........................] - ETA: 0s - loss: 0.2393 - mse: 194.2256
19/89 [=====>........................] - ETA: 0s - loss: 0.2405 - mse: 193.0424
25/89 [=======>......................] - ETA: 0s - loss: 0.2406 - mse: 191.8665
31/89 [=========>....................] - ETA: 0s - loss: 0.2361 - mse: 190.5175
37/89 [===========>..................] - ETA: 0s - loss: 0.2279 - mse: 189.0524
43/89 [=============>................] - ETA: 0s - loss: 0.2299 - mse: 190.5767
49/89 [===============>..............] - ETA: 0s - loss: 0.2262 - mse: 190.2483
55/89 [=================>............] - ETA: 0s - loss: 0.2213 - mse: 190.9912
61/89 [===================>..........] - ETA: 0s - loss: 0.2160 - mse: 191.1128
67/89 [=====================>........] - ETA: 0s - loss: 0.2107 - mse: 192.0579
73/89 [=======================>......] - ETA: 0s - loss: 0.2051 - mse: 191.6132
79/89 [=========================>....] - ETA: 0s - loss: 0.2034 - mse: 191.6247
85/89 [===========================>..] - ETA: 0s - loss: 0.1993 - mse: 191.3325
89/89 [==============================] - 1s 9ms/step - loss: 0.1989 - mse: 191.6196

89/89 [==============================] - 1s 10ms/step - loss: 0.1989 - mse: 191.6196 - val_loss: 0.7831 - val_mse: 188.1819
Epoch 30/30

 1/89 [..............................] - ETA: 0s - loss: 0.1706 - mse: 217.9918
 7/89 [=>............................] - ETA: 0s - loss: 0.1682 - mse: 199.7069
13/89 [===>..........................] - ETA: 0s - loss: 0.1647 - mse: 195.0325
19/89 [=====>........................] - ETA: 0s - loss: 0.1612 - mse: 190.1889
25/89 [=======>......................] - ETA: 0s - loss: 0.1569 - mse: 193.7515
31/89 [=========>....................] - ETA: 0s - loss: 0.1537 - mse: 193.1474
37/89 [===========>..................] - ETA: 0s - loss: 0.1538 - mse: 190.9355
43/89 [=============>................] - ETA: 0s - loss: 0.1547 - mse: 191.2996
49/89 [===============>..............] - ETA: 0s - loss: 0.1550 - mse: 189.9469
55/89 [=================>............] - ETA: 0s - loss: 0.1583 - mse: 189.6576
61/89 [===================>..........] - ETA: 0s - loss: 0.1593 - mse: 189.1916
67/89 [=====================>........] - ETA: 0s - loss: 0.1577 - mse: 190.1339
73/89 [=======================>......] - ETA: 0s - loss: 0.1573 - mse: 190.4627
79/89 [=========================>....] - ETA: 0s - loss: 0.1572 - mse: 190.8852
85/89 [===========================>..] - ETA: 0s - loss: 0.1614 - mse: 191.6549
89/89 [==============================] - 1s 9ms/step - loss: 0.1616 - mse: 191.6197

89/89 [==============================] - 1s 11ms/step - loss: 0.1616 - mse: 191.6197 - val_loss: 0.9165 - val_mse: 188.1821

library(tfruns)

bike_runs <- tuning_run("bike_tune.R",
                   flags = list(
                     nodes = c(64, 128, 392),
                     learning_rate = c(0.01, 0.05, 0.001, 0.0001),
                     batch_size= c(100, 200, 500, 1000),
                     epochs = c(30,50,100),
                     activation = c("relu", "sigmoid", "tanh")
                   ),
                   sample = 0.02
)

432 total combinations of flags 
(sampled to 9 combinations)

Y

Training run 1/9 (flags = list(128, 1e-04, 500, 100, "tanh")) 
Using run directory runs/2023-04-03T22-31-36Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 106) %>%
+   layer_dense(units = FLAGS$nodes, activation .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('mse')
+  .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   second_bikes_matrix, second_bikes_train_set$count, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(a .... [TRUNCATED] 
Epoch 1/100

 1/18 [>.............................] - ETA: 5s - loss: 4.7286 - mse: 189.7984
10/18 [===============>..............] - ETA: 0s - loss: 4.0468 - mse: 190.8999
18/18 [==============================] - 0s 6ms/step - loss: 3.7387 - mse: 191.6116

18/18 [==============================] - 1s 43ms/step - loss: 3.7387 - mse: 191.6116 - val_loss: 3.1186 - val_mse: 188.1745
Epoch 2/100

 1/18 [>.............................] - ETA: 0s - loss: 3.1635 - mse: 196.9254
10/18 [===============>..............] - ETA: 0s - loss: 3.0114 - mse: 192.8468
18/18 [==============================] - 0s 6ms/step - loss: 2.9130 - mse: 191.6118

18/18 [==============================] - 0s 16ms/step - loss: 2.9130 - mse: 191.6118 - val_loss: 2.6739 - val_mse: 188.1748
Epoch 3/100

 1/18 [>.............................] - ETA: 0s - loss: 2.6485 - mse: 181.8944
 9/18 [==============>...............] - ETA: 0s - loss: 2.6022 - mse: 195.1649
18/18 [==============================] - 0s 6ms/step - loss: 2.5299 - mse: 191.6120

18/18 [==============================] - 0s 16ms/step - loss: 2.5299 - mse: 191.6120 - val_loss: 2.4002 - val_mse: 188.1750
Epoch 4/100

 1/18 [>.............................] - ETA: 0s - loss: 2.3677 - mse: 190.9609
10/18 [===============>..............] - ETA: 0s - loss: 2.3150 - mse: 194.0014
18/18 [==============================] - 0s 6ms/step - loss: 2.2674 - mse: 191.6123

18/18 [==============================] - 0s 14ms/step - loss: 2.2674 - mse: 191.6123 - val_loss: 2.2118 - val_mse: 188.1752
Epoch 5/100

 1/18 [>.............................] - ETA: 0s - loss: 2.1326 - mse: 186.7803
11/18 [=================>............] - ETA: 0s - loss: 2.1003 - mse: 191.9422
18/18 [==============================] - 0s 5ms/step - loss: 2.0679 - mse: 191.6124

18/18 [==============================] - 0s 14ms/step - loss: 2.0679 - mse: 191.6124 - val_loss: 2.0538 - val_mse: 188.1754
Epoch 6/100

 1/18 [>.............................] - ETA: 0s - loss: 1.9730 - mse: 196.4866
11/18 [=================>............] - ETA: 0s - loss: 1.9483 - mse: 194.9746
18/18 [==============================] - 0s 6ms/step - loss: 1.9103 - mse: 191.6126

18/18 [==============================] - 0s 14ms/step - loss: 1.9103 - mse: 191.6126 - val_loss: 1.9007 - val_mse: 188.1755
Epoch 7/100

 1/18 [>.............................] - ETA: 0s - loss: 1.8086 - mse: 181.6443
11/18 [=================>............] - ETA: 0s - loss: 1.7883 - mse: 189.5527
18/18 [==============================] - 0s 5ms/step - loss: 1.7747 - mse: 191.6127

18/18 [==============================] - 0s 14ms/step - loss: 1.7747 - mse: 191.6127 - val_loss: 1.7668 - val_mse: 188.1756
Epoch 8/100

 1/18 [>.............................] - ETA: 0s - loss: 1.7106 - mse: 187.7155
10/18 [===============>..............] - ETA: 0s - loss: 1.6789 - mse: 190.9494
18/18 [==============================] - 0s 6ms/step - loss: 1.6587 - mse: 191.6129

18/18 [==============================] - 0s 15ms/step - loss: 1.6587 - mse: 191.6129 - val_loss: 1.6514 - val_mse: 188.1758
Epoch 9/100

 1/18 [>.............................] - ETA: 0s - loss: 1.5624 - mse: 179.9027
10/18 [===============>..............] - ETA: 0s - loss: 1.5727 - mse: 190.9096
18/18 [==============================] - 0s 6ms/step - loss: 1.5523 - mse: 191.6131

18/18 [==============================] - 0s 15ms/step - loss: 1.5523 - mse: 191.6131 - val_loss: 1.5378 - val_mse: 188.1759
Epoch 10/100

 1/18 [>.............................] - ETA: 0s - loss: 1.4844 - mse: 184.5411
10/18 [===============>..............] - ETA: 0s - loss: 1.4689 - mse: 188.8345
18/18 [==============================] - 0s 6ms/step - loss: 1.4587 - mse: 191.6132

18/18 [==============================] - 0s 15ms/step - loss: 1.4587 - mse: 191.6132 - val_loss: 1.4386 - val_mse: 188.1761
Epoch 11/100

 1/18 [>.............................] - ETA: 0s - loss: 1.3884 - mse: 181.8925
10/18 [===============>..............] - ETA: 0s - loss: 1.3878 - mse: 191.8227
18/18 [==============================] - 0s 6ms/step - loss: 1.3734 - mse: 191.6134

18/18 [==============================] - 0s 14ms/step - loss: 1.3734 - mse: 191.6134 - val_loss: 1.3573 - val_mse: 188.1763
Epoch 12/100

 1/18 [>.............................] - ETA: 0s - loss: 1.3327 - mse: 195.2634
11/18 [=================>............] - ETA: 0s - loss: 1.3087 - mse: 191.9703
18/18 [==============================] - 0s 6ms/step - loss: 1.2949 - mse: 191.6136

18/18 [==============================] - 0s 14ms/step - loss: 1.2949 - mse: 191.6136 - val_loss: 1.2772 - val_mse: 188.1764
Epoch 13/100

 1/18 [>.............................] - ETA: 0s - loss: 1.2742 - mse: 198.6427
10/18 [===============>..............] - ETA: 0s - loss: 1.2294 - mse: 188.5903
18/18 [==============================] - 0s 6ms/step - loss: 1.2233 - mse: 191.6137

18/18 [==============================] - 0s 15ms/step - loss: 1.2233 - mse: 191.6137 - val_loss: 1.2042 - val_mse: 188.1766
Epoch 14/100

 1/18 [>.............................] - ETA: 0s - loss: 1.2085 - mse: 198.2248
10/18 [===============>..............] - ETA: 0s - loss: 1.1790 - mse: 192.4350
18/18 [==============================] - 0s 6ms/step - loss: 1.1618 - mse: 191.6139

18/18 [==============================] - 0s 15ms/step - loss: 1.1618 - mse: 191.6139 - val_loss: 1.1608 - val_mse: 188.1767
Epoch 15/100

 1/18 [>.............................] - ETA: 0s - loss: 1.1595 - mse: 198.5444
11/18 [=================>............] - ETA: 0s - loss: 1.1160 - mse: 192.9587
18/18 [==============================] - 0s 5ms/step - loss: 1.1020 - mse: 191.6140

18/18 [==============================] - 0s 14ms/step - loss: 1.1020 - mse: 191.6140 - val_loss: 1.1030 - val_mse: 188.1769
Epoch 16/100

 1/18 [>.............................] - ETA: 0s - loss: 1.0906 - mse: 200.3158
10/18 [===============>..............] - ETA: 0s - loss: 1.0591 - mse: 192.4403
18/18 [==============================] - 0s 5ms/step - loss: 1.0453 - mse: 191.6142

18/18 [==============================] - 0s 15ms/step - loss: 1.0453 - mse: 191.6142 - val_loss: 1.0438 - val_mse: 188.1770
Epoch 17/100

 1/18 [>.............................] - ETA: 0s - loss: 1.0257 - mse: 190.6557
11/18 [=================>............] - ETA: 0s - loss: 0.9995 - mse: 191.0505
18/18 [==============================] - 0s 5ms/step - loss: 0.9956 - mse: 191.6143

18/18 [==============================] - 0s 15ms/step - loss: 0.9956 - mse: 191.6143 - val_loss: 0.9879 - val_mse: 188.1772
Epoch 18/100

 1/18 [>.............................] - ETA: 0s - loss: 0.9886 - mse: 200.0854
10/18 [===============>..............] - ETA: 0s - loss: 0.9696 - mse: 194.4794
18/18 [==============================] - 0s 6ms/step - loss: 0.9516 - mse: 191.6145

18/18 [==============================] - 0s 15ms/step - loss: 0.9516 - mse: 191.6145 - val_loss: 0.9659 - val_mse: 188.1773
Epoch 19/100

 1/18 [>.............................] - ETA: 0s - loss: 0.8968 - mse: 186.3824
11/18 [=================>............] - ETA: 0s - loss: 0.9151 - mse: 192.1530
18/18 [==============================] - 0s 5ms/step - loss: 0.9085 - mse: 191.6146

18/18 [==============================] - 0s 14ms/step - loss: 0.9085 - mse: 191.6146 - val_loss: 0.9084 - val_mse: 188.1774
Epoch 20/100

 1/18 [>.............................] - ETA: 0s - loss: 0.8704 - mse: 188.5450
10/18 [===============>..............] - ETA: 0s - loss: 0.8837 - mse: 193.9145
18/18 [==============================] - 0s 5ms/step - loss: 0.8680 - mse: 191.6148

18/18 [==============================] - 0s 15ms/step - loss: 0.8680 - mse: 191.6148 - val_loss: 0.8722 - val_mse: 188.1776
Epoch 21/100

 1/18 [>.............................] - ETA: 0s - loss: 0.8761 - mse: 202.2218
11/18 [=================>............] - ETA: 0s - loss: 0.8364 - mse: 192.3887
18/18 [==============================] - 0s 5ms/step - loss: 0.8292 - mse: 191.6149

18/18 [==============================] - 0s 15ms/step - loss: 0.8292 - mse: 191.6149 - val_loss: 0.8352 - val_mse: 188.1777
Epoch 22/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7686 - mse: 180.0685
10/18 [===============>..............] - ETA: 0s - loss: 0.7947 - mse: 188.7833
18/18 [==============================] - 0s 6ms/step - loss: 0.7953 - mse: 191.6150

18/18 [==============================] - 0s 15ms/step - loss: 0.7953 - mse: 191.6150 - val_loss: 0.8132 - val_mse: 188.1779
Epoch 23/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7920 - mse: 196.9218
10/18 [===============>..............] - ETA: 0s - loss: 0.7677 - mse: 191.4559
18/18 [==============================] - 0s 6ms/step - loss: 0.7633 - mse: 191.6152

18/18 [==============================] - 0s 15ms/step - loss: 0.7633 - mse: 191.6152 - val_loss: 0.7752 - val_mse: 188.1780
Epoch 24/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7270 - mse: 182.4856
10/18 [===============>..............] - ETA: 0s - loss: 0.7384 - mse: 191.9183
18/18 [==============================] - 0s 5ms/step - loss: 0.7338 - mse: 191.6153

18/18 [==============================] - 0s 14ms/step - loss: 0.7338 - mse: 191.6153 - val_loss: 0.7697 - val_mse: 188.1781
Epoch 25/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7557 - mse: 205.1565
10/18 [===============>..............] - ETA: 0s - loss: 0.7128 - mse: 191.8396
18/18 [==============================] - 0s 5ms/step - loss: 0.7034 - mse: 191.6154

18/18 [==============================] - 0s 15ms/step - loss: 0.7034 - mse: 191.6154 - val_loss: 0.7246 - val_mse: 188.1783
Epoch 26/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7063 - mse: 197.6393
10/18 [===============>..............] - ETA: 0s - loss: 0.6818 - mse: 192.2428
18/18 [==============================] - 0s 6ms/step - loss: 0.6777 - mse: 191.6156

18/18 [==============================] - 0s 15ms/step - loss: 0.6777 - mse: 191.6156 - val_loss: 0.7036 - val_mse: 188.1784
Epoch 27/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7017 - mse: 200.9848
 9/18 [==============>...............] - ETA: 0s - loss: 0.6624 - mse: 193.4892
18/18 [==============================] - 0s 6ms/step - loss: 0.6521 - mse: 191.6157

18/18 [==============================] - 0s 15ms/step - loss: 0.6521 - mse: 191.6157 - val_loss: 0.6819 - val_mse: 188.1785
Epoch 28/100

 1/18 [>.............................] - ETA: 0s - loss: 0.6361 - mse: 187.1849
11/18 [=================>............] - ETA: 0s - loss: 0.6323 - mse: 191.5957
18/18 [==============================] - 0s 5ms/step - loss: 0.6282 - mse: 191.6158

18/18 [==============================] - 0s 15ms/step - loss: 0.6282 - mse: 191.6158 - val_loss: 0.6464 - val_mse: 188.1786
Epoch 29/100

 1/18 [>.............................] - ETA: 0s - loss: 0.6147 - mse: 187.6056
10/18 [===============>..............] - ETA: 0s - loss: 0.6087 - mse: 190.6030
18/18 [==============================] - 0s 6ms/step - loss: 0.6058 - mse: 191.6159

18/18 [==============================] - 0s 15ms/step - loss: 0.6058 - mse: 191.6159 - val_loss: 0.6315 - val_mse: 188.1787
Epoch 30/100

 1/18 [>.............................] - ETA: 0s - loss: 0.6048 - mse: 200.1790
10/18 [===============>..............] - ETA: 0s - loss: 0.5920 - mse: 192.5500
18/18 [==============================] - 0s 5ms/step - loss: 0.5850 - mse: 191.6161

18/18 [==============================] - 0s 15ms/step - loss: 0.5850 - mse: 191.6161 - val_loss: 0.6163 - val_mse: 188.1788
Epoch 31/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5842 - mse: 196.1522
11/18 [=================>............] - ETA: 0s - loss: 0.5696 - mse: 192.2411
18/18 [==============================] - 0s 5ms/step - loss: 0.5654 - mse: 191.6162

18/18 [==============================] - 0s 15ms/step - loss: 0.5654 - mse: 191.6162 - val_loss: 0.5864 - val_mse: 188.1789
Epoch 32/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5358 - mse: 187.3543
10/18 [===============>..............] - ETA: 0s - loss: 0.5491 - mse: 190.8376
18/18 [==============================] - 0s 6ms/step - loss: 0.5471 - mse: 191.6163

18/18 [==============================] - 0s 14ms/step - loss: 0.5471 - mse: 191.6163 - val_loss: 0.5897 - val_mse: 188.1790
Epoch 33/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5060 - mse: 183.8002
10/18 [===============>..............] - ETA: 0s - loss: 0.5289 - mse: 191.3027
18/18 [==============================] - 0s 6ms/step - loss: 0.5306 - mse: 191.6164

18/18 [==============================] - 0s 15ms/step - loss: 0.5306 - mse: 191.6164 - val_loss: 0.5682 - val_mse: 188.1791
Epoch 34/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4932 - mse: 184.4258
11/18 [=================>............] - ETA: 0s - loss: 0.5167 - mse: 191.3063
18/18 [==============================] - 0s 6ms/step - loss: 0.5145 - mse: 191.6165

18/18 [==============================] - 0s 14ms/step - loss: 0.5145 - mse: 191.6165 - val_loss: 0.5475 - val_mse: 188.1792
Epoch 35/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4926 - mse: 189.2462
10/18 [===============>..............] - ETA: 0s - loss: 0.4962 - mse: 191.2307
18/18 [==============================] - 0s 6ms/step - loss: 0.4957 - mse: 191.6166

18/18 [==============================] - 0s 15ms/step - loss: 0.4957 - mse: 191.6166 - val_loss: 0.5215 - val_mse: 188.1793
Epoch 36/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5094 - mse: 203.1571
10/18 [===============>..............] - ETA: 0s - loss: 0.4775 - mse: 190.4384
18/18 [==============================] - 0s 6ms/step - loss: 0.4816 - mse: 191.6167

18/18 [==============================] - 0s 15ms/step - loss: 0.4816 - mse: 191.6167 - val_loss: 0.5356 - val_mse: 188.1794
Epoch 37/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4827 - mse: 197.9358
10/18 [===============>..............] - ETA: 0s - loss: 0.4793 - mse: 194.1311
18/18 [==============================] - 0s 6ms/step - loss: 0.4696 - mse: 191.6167

18/18 [==============================] - 0s 16ms/step - loss: 0.4696 - mse: 191.6167 - val_loss: 0.5113 - val_mse: 188.1795
Epoch 38/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4698 - mse: 197.0878
10/18 [===============>..............] - ETA: 0s - loss: 0.4477 - mse: 191.7968
18/18 [==============================] - 0s 6ms/step - loss: 0.4529 - mse: 191.6169

18/18 [==============================] - 0s 15ms/step - loss: 0.4529 - mse: 191.6169 - val_loss: 0.5160 - val_mse: 188.1796
Epoch 39/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4671 - mse: 195.1422
10/18 [===============>..............] - ETA: 0s - loss: 0.4493 - mse: 193.5503
18/18 [==============================] - 0s 6ms/step - loss: 0.4408 - mse: 191.6170

18/18 [==============================] - 0s 15ms/step - loss: 0.4408 - mse: 191.6170 - val_loss: 0.4908 - val_mse: 188.1797
Epoch 40/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4132 - mse: 184.0584
10/18 [===============>..............] - ETA: 0s - loss: 0.4303 - mse: 191.0027
18/18 [==============================] - 0s 5ms/step - loss: 0.4296 - mse: 191.6171

18/18 [==============================] - 0s 15ms/step - loss: 0.4296 - mse: 191.6171 - val_loss: 0.4801 - val_mse: 188.1797
Epoch 41/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4132 - mse: 190.3211
10/18 [===============>..............] - ETA: 0s - loss: 0.4332 - mse: 195.6871
18/18 [==============================] - 0s 6ms/step - loss: 0.4199 - mse: 191.6171

18/18 [==============================] - 0s 16ms/step - loss: 0.4199 - mse: 191.6171 - val_loss: 0.4619 - val_mse: 188.1798
Epoch 42/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3672 - mse: 178.2244
10/18 [===============>..............] - ETA: 0s - loss: 0.4086 - mse: 191.7907
18/18 [==============================] - 0s 6ms/step - loss: 0.4061 - mse: 191.6172

18/18 [==============================] - 0s 16ms/step - loss: 0.4061 - mse: 191.6172 - val_loss: 0.4561 - val_mse: 188.1799
Epoch 43/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4168 - mse: 197.5151
10/18 [===============>..............] - ETA: 0s - loss: 0.3963 - mse: 192.4903
18/18 [==============================] - 0s 6ms/step - loss: 0.3942 - mse: 191.6173

18/18 [==============================] - 0s 15ms/step - loss: 0.3942 - mse: 191.6173 - val_loss: 0.4410 - val_mse: 188.1800
Epoch 44/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3606 - mse: 183.7324
10/18 [===============>..............] - ETA: 0s - loss: 0.3891 - mse: 191.0107
18/18 [==============================] - 0s 6ms/step - loss: 0.3858 - mse: 191.6173

18/18 [==============================] - 0s 15ms/step - loss: 0.3858 - mse: 191.6173 - val_loss: 0.4422 - val_mse: 188.1800
Epoch 45/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3633 - mse: 191.1322
 9/18 [==============>...............] - ETA: 0s - loss: 0.3663 - mse: 189.6767
17/18 [===========================>..] - ETA: 0s - loss: 0.3740 - mse: 192.1490
18/18 [==============================] - 0s 6ms/step - loss: 0.3730 - mse: 191.6174

18/18 [==============================] - 0s 15ms/step - loss: 0.3730 - mse: 191.6174 - val_loss: 0.4390 - val_mse: 188.1801
Epoch 46/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3684 - mse: 193.0142
 9/18 [==============>...............] - ETA: 0s - loss: 0.3663 - mse: 189.6725
17/18 [===========================>..] - ETA: 0s - loss: 0.3671 - mse: 191.9741
18/18 [==============================] - 0s 7ms/step - loss: 0.3663 - mse: 191.6175

18/18 [==============================] - 0s 16ms/step - loss: 0.3663 - mse: 191.6175 - val_loss: 0.4217 - val_mse: 188.1802
Epoch 47/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3630 - mse: 198.9762
10/18 [===============>..............] - ETA: 0s - loss: 0.3563 - mse: 190.4299
18/18 [==============================] - 0s 6ms/step - loss: 0.3558 - mse: 191.6175

18/18 [==============================] - 0s 15ms/step - loss: 0.3558 - mse: 191.6175 - val_loss: 0.4185 - val_mse: 188.1802
Epoch 48/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3510 - mse: 198.8804
 9/18 [==============>...............] - ETA: 0s - loss: 0.3512 - mse: 191.6232
18/18 [==============================] - 0s 6ms/step - loss: 0.3483 - mse: 191.6176

18/18 [==============================] - 0s 15ms/step - loss: 0.3483 - mse: 191.6176 - val_loss: 0.3972 - val_mse: 188.1803
Epoch 49/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3511 - mse: 197.6958
10/18 [===============>..............] - ETA: 0s - loss: 0.3410 - mse: 192.9768
18/18 [==============================] - 0s 6ms/step - loss: 0.3391 - mse: 191.6177

18/18 [==============================] - 0s 15ms/step - loss: 0.3391 - mse: 191.6177 - val_loss: 0.4063 - val_mse: 188.1803
Epoch 50/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3467 - mse: 191.2259
10/18 [===============>..............] - ETA: 0s - loss: 0.3287 - mse: 190.5260
18/18 [==============================] - 0s 6ms/step - loss: 0.3316 - mse: 191.6177

18/18 [==============================] - 0s 14ms/step - loss: 0.3316 - mse: 191.6177 - val_loss: 0.3859 - val_mse: 188.1804
Epoch 51/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2851 - mse: 177.6569
10/18 [===============>..............] - ETA: 0s - loss: 0.3205 - mse: 190.1015
18/18 [==============================] - 0s 6ms/step - loss: 0.3229 - mse: 191.6178

18/18 [==============================] - 0s 15ms/step - loss: 0.3229 - mse: 191.6178 - val_loss: 0.3765 - val_mse: 188.1805
Epoch 52/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2953 - mse: 180.0428
 9/18 [==============>...............] - ETA: 0s - loss: 0.3161 - mse: 191.0613
17/18 [===========================>..] - ETA: 0s - loss: 0.3178 - mse: 192.7124
18/18 [==============================] - 0s 6ms/step - loss: 0.3163 - mse: 191.6178

18/18 [==============================] - 0s 16ms/step - loss: 0.3163 - mse: 191.6178 - val_loss: 0.4161 - val_mse: 188.1805
Epoch 53/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3183 - mse: 193.0276
10/18 [===============>..............] - ETA: 0s - loss: 0.3150 - mse: 192.2077
18/18 [==============================] - 0s 6ms/step - loss: 0.3114 - mse: 191.6179

18/18 [==============================] - 0s 15ms/step - loss: 0.3114 - mse: 191.6179 - val_loss: 0.4090 - val_mse: 188.1805
Epoch 54/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3075 - mse: 190.8442
10/18 [===============>..............] - ETA: 0s - loss: 0.3044 - mse: 192.4241
18/18 [==============================] - 0s 6ms/step - loss: 0.3016 - mse: 191.6180

18/18 [==============================] - 0s 14ms/step - loss: 0.3016 - mse: 191.6180 - val_loss: 0.3564 - val_mse: 188.1806
Epoch 55/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2940 - mse: 184.5150
10/18 [===============>..............] - ETA: 0s - loss: 0.2933 - mse: 192.2908
18/18 [==============================] - 0s 6ms/step - loss: 0.2946 - mse: 191.6180

18/18 [==============================] - 0s 15ms/step - loss: 0.2946 - mse: 191.6180 - val_loss: 0.3511 - val_mse: 188.1806
Epoch 56/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2595 - mse: 181.1576
 9/18 [==============>...............] - ETA: 0s - loss: 0.2857 - mse: 190.0283
18/18 [==============================] - 0s 6ms/step - loss: 0.2862 - mse: 191.6181

18/18 [==============================] - 0s 15ms/step - loss: 0.2862 - mse: 191.6181 - val_loss: 0.3542 - val_mse: 188.1807
Epoch 57/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2617 - mse: 177.1938
10/18 [===============>..............] - ETA: 0s - loss: 0.2866 - mse: 192.9492
18/18 [==============================] - 0s 6ms/step - loss: 0.2833 - mse: 191.6181

18/18 [==============================] - 0s 15ms/step - loss: 0.2833 - mse: 191.6181 - val_loss: 0.3804 - val_mse: 188.1807
Epoch 58/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2753 - mse: 193.8072
10/18 [===============>..............] - ETA: 0s - loss: 0.2701 - mse: 188.8690
18/18 [==============================] - 0s 6ms/step - loss: 0.2789 - mse: 191.6182

18/18 [==============================] - 0s 14ms/step - loss: 0.2789 - mse: 191.6182 - val_loss: 0.3332 - val_mse: 188.1807
Epoch 59/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2561 - mse: 182.1628
10/18 [===============>..............] - ETA: 0s - loss: 0.2761 - mse: 192.1598
18/18 [==============================] - 0s 6ms/step - loss: 0.2720 - mse: 191.6182

18/18 [==============================] - 0s 15ms/step - loss: 0.2720 - mse: 191.6182 - val_loss: 0.3650 - val_mse: 188.1808
Epoch 60/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2741 - mse: 197.7493
 9/18 [==============>...............] - ETA: 0s - loss: 0.2594 - mse: 192.1250
18/18 [==============================] - 0s 6ms/step - loss: 0.2639 - mse: 191.6183

18/18 [==============================] - 0s 15ms/step - loss: 0.2639 - mse: 191.6183 - val_loss: 0.3621 - val_mse: 188.1809
Epoch 61/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2509 - mse: 191.3874
10/18 [===============>..............] - ETA: 0s - loss: 0.2623 - mse: 191.0591
18/18 [==============================] - 0s 6ms/step - loss: 0.2631 - mse: 191.6183

18/18 [==============================] - 0s 15ms/step - loss: 0.2631 - mse: 191.6183 - val_loss: 0.3193 - val_mse: 188.1809
Epoch 62/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2621 - mse: 189.8344
10/18 [===============>..............] - ETA: 0s - loss: 0.2596 - mse: 193.4127
18/18 [==============================] - 0s 6ms/step - loss: 0.2565 - mse: 191.6183

18/18 [==============================] - 0s 14ms/step - loss: 0.2565 - mse: 191.6183 - val_loss: 0.3969 - val_mse: 188.1810
Epoch 63/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2433 - mse: 191.0660
10/18 [===============>..............] - ETA: 0s - loss: 0.2426 - mse: 190.1535
18/18 [==============================] - 0s 6ms/step - loss: 0.2486 - mse: 191.6184

18/18 [==============================] - 0s 15ms/step - loss: 0.2486 - mse: 191.6184 - val_loss: 0.3187 - val_mse: 188.1810
Epoch 64/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2302 - mse: 187.9501
10/18 [===============>..............] - ETA: 0s - loss: 0.2387 - mse: 189.6483
18/18 [==============================] - 0s 6ms/step - loss: 0.2429 - mse: 191.6184

18/18 [==============================] - 0s 15ms/step - loss: 0.2429 - mse: 191.6184 - val_loss: 0.3107 - val_mse: 188.1810
Epoch 65/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2211 - mse: 183.8060
10/18 [===============>..............] - ETA: 0s - loss: 0.2347 - mse: 190.1352
18/18 [==============================] - 0s 6ms/step - loss: 0.2380 - mse: 191.6185

18/18 [==============================] - 0s 14ms/step - loss: 0.2380 - mse: 191.6185 - val_loss: 0.3349 - val_mse: 188.1811
Epoch 66/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2260 - mse: 179.2921
10/18 [===============>..............] - ETA: 0s - loss: 0.2401 - mse: 191.5217
18/18 [==============================] - 0s 6ms/step - loss: 0.2379 - mse: 191.6185

18/18 [==============================] - 0s 15ms/step - loss: 0.2379 - mse: 191.6185 - val_loss: 0.3233 - val_mse: 188.1811
Epoch 67/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2279 - mse: 191.0221
10/18 [===============>..............] - ETA: 0s - loss: 0.2252 - mse: 192.1047
18/18 [==============================] - 0s 6ms/step - loss: 0.2265 - mse: 191.6185

18/18 [==============================] - 0s 15ms/step - loss: 0.2265 - mse: 191.6185 - val_loss: 0.3151 - val_mse: 188.1811
Epoch 68/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2145 - mse: 188.5072
10/18 [===============>..............] - ETA: 0s - loss: 0.2217 - mse: 189.8411
18/18 [==============================] - 0s 6ms/step - loss: 0.2245 - mse: 191.6186

18/18 [==============================] - 0s 15ms/step - loss: 0.2245 - mse: 191.6186 - val_loss: 0.3036 - val_mse: 188.1812
Epoch 69/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2004 - mse: 184.2873
10/18 [===============>..............] - ETA: 0s - loss: 0.2199 - mse: 192.5303
18/18 [==============================] - 0s 6ms/step - loss: 0.2200 - mse: 191.6186

18/18 [==============================] - 0s 15ms/step - loss: 0.2200 - mse: 191.6186 - val_loss: 0.3117 - val_mse: 188.1812
Epoch 70/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2085 - mse: 193.5948
10/18 [===============>..............] - ETA: 0s - loss: 0.2117 - mse: 192.3942
18/18 [==============================] - 0s 6ms/step - loss: 0.2150 - mse: 191.6187

18/18 [==============================] - 0s 14ms/step - loss: 0.2150 - mse: 191.6187 - val_loss: 0.2953 - val_mse: 188.1812
Epoch 71/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2241 - mse: 185.1745
10/18 [===============>..............] - ETA: 0s - loss: 0.2150 - mse: 191.2537
18/18 [==============================] - 0s 6ms/step - loss: 0.2135 - mse: 191.6187

18/18 [==============================] - 0s 14ms/step - loss: 0.2135 - mse: 191.6187 - val_loss: 0.3059 - val_mse: 188.1813
Epoch 72/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2146 - mse: 195.7450
10/18 [===============>..............] - ETA: 0s - loss: 0.2019 - mse: 191.9853
18/18 [==============================] - 0s 6ms/step - loss: 0.2078 - mse: 191.6187

18/18 [==============================] - 0s 15ms/step - loss: 0.2078 - mse: 191.6187 - val_loss: 0.2889 - val_mse: 188.1812
Epoch 73/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1975 - mse: 194.6444
10/18 [===============>..............] - ETA: 0s - loss: 0.2049 - mse: 194.5032
18/18 [==============================] - 0s 6ms/step - loss: 0.2049 - mse: 191.6188

18/18 [==============================] - 0s 15ms/step - loss: 0.2049 - mse: 191.6188 - val_loss: 0.2821 - val_mse: 188.1813
Epoch 74/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1997 - mse: 196.8254
10/18 [===============>..............] - ETA: 0s - loss: 0.2049 - mse: 192.1586
18/18 [==============================] - 0s 6ms/step - loss: 0.2026 - mse: 191.6188

18/18 [==============================] - 0s 14ms/step - loss: 0.2026 - mse: 191.6188 - val_loss: 0.3381 - val_mse: 188.1813
Epoch 75/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2211 - mse: 205.4344
10/18 [===============>..............] - ETA: 0s - loss: 0.1949 - mse: 190.9831
18/18 [==============================] - 0s 6ms/step - loss: 0.1949 - mse: 191.6188

18/18 [==============================] - 0s 15ms/step - loss: 0.1949 - mse: 191.6188 - val_loss: 0.2788 - val_mse: 188.1813
Epoch 76/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2059 - mse: 189.5867
10/18 [===============>..............] - ETA: 0s - loss: 0.1895 - mse: 192.7278
18/18 [==============================] - 0s 6ms/step - loss: 0.1918 - mse: 191.6189

18/18 [==============================] - 0s 15ms/step - loss: 0.1918 - mse: 191.6189 - val_loss: 0.2763 - val_mse: 188.1814
Epoch 77/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1803 - mse: 193.4144
10/18 [===============>..............] - ETA: 0s - loss: 0.1893 - mse: 193.3636
18/18 [==============================] - 0s 6ms/step - loss: 0.1892 - mse: 191.6189

18/18 [==============================] - 0s 14ms/step - loss: 0.1892 - mse: 191.6189 - val_loss: 0.2723 - val_mse: 188.1814
Epoch 78/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1608 - mse: 177.6287
10/18 [===============>..............] - ETA: 0s - loss: 0.1825 - mse: 191.3292
18/18 [==============================] - 0s 6ms/step - loss: 0.1842 - mse: 191.6189

18/18 [==============================] - 0s 15ms/step - loss: 0.1842 - mse: 191.6189 - val_loss: 0.2945 - val_mse: 188.1814
Epoch 79/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1894 - mse: 191.8609
10/18 [===============>..............] - ETA: 0s - loss: 0.1756 - mse: 188.1969
18/18 [==============================] - 0s 6ms/step - loss: 0.1807 - mse: 191.6189

18/18 [==============================] - 0s 15ms/step - loss: 0.1807 - mse: 191.6189 - val_loss: 0.2711 - val_mse: 188.1815
Epoch 80/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1511 - mse: 178.3186
10/18 [===============>..............] - ETA: 0s - loss: 0.1695 - mse: 189.3596
18/18 [==============================] - 0s 6ms/step - loss: 0.1776 - mse: 191.6190

18/18 [==============================] - 0s 15ms/step - loss: 0.1776 - mse: 191.6190 - val_loss: 0.2938 - val_mse: 188.1815
Epoch 81/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1464 - mse: 179.5293
10/18 [===============>..............] - ETA: 0s - loss: 0.1748 - mse: 191.4472
18/18 [==============================] - 0s 6ms/step - loss: 0.1743 - mse: 191.6190

18/18 [==============================] - 0s 15ms/step - loss: 0.1743 - mse: 191.6190 - val_loss: 0.2704 - val_mse: 188.1815
Epoch 82/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1690 - mse: 188.9019
10/18 [===============>..............] - ETA: 0s - loss: 0.1786 - mse: 194.9192
18/18 [==============================] - 0s 6ms/step - loss: 0.1726 - mse: 191.6190

18/18 [==============================] - 0s 14ms/step - loss: 0.1726 - mse: 191.6190 - val_loss: 0.2750 - val_mse: 188.1815
Epoch 83/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1648 - mse: 194.6610
10/18 [===============>..............] - ETA: 0s - loss: 0.1744 - mse: 194.2496
18/18 [==============================] - 0s 6ms/step - loss: 0.1720 - mse: 191.6190

18/18 [==============================] - 0s 15ms/step - loss: 0.1720 - mse: 191.6190 - val_loss: 0.2670 - val_mse: 188.1815
Epoch 84/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1870 - mse: 199.2828
10/18 [===============>..............] - ETA: 0s - loss: 0.1661 - mse: 191.4848
18/18 [==============================] - 0s 6ms/step - loss: 0.1680 - mse: 191.6191

18/18 [==============================] - 0s 15ms/step - loss: 0.1680 - mse: 191.6191 - val_loss: 0.3159 - val_mse: 188.1815
Epoch 85/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1513 - mse: 187.5560
10/18 [===============>..............] - ETA: 0s - loss: 0.1670 - mse: 193.7921
18/18 [==============================] - 0s 6ms/step - loss: 0.1652 - mse: 191.6191

18/18 [==============================] - 0s 15ms/step - loss: 0.1652 - mse: 191.6191 - val_loss: 0.2584 - val_mse: 188.1816
Epoch 86/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1486 - mse: 179.8855
10/18 [===============>..............] - ETA: 0s - loss: 0.1618 - mse: 191.1056
18/18 [==============================] - 0s 6ms/step - loss: 0.1626 - mse: 191.6191

18/18 [==============================] - 0s 16ms/step - loss: 0.1626 - mse: 191.6191 - val_loss: 0.2418 - val_mse: 188.1816
Epoch 87/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1667 - mse: 195.9711
 9/18 [==============>...............] - ETA: 0s - loss: 0.1621 - mse: 194.0093
18/18 [==============================] - 0s 6ms/step - loss: 0.1630 - mse: 191.6191

18/18 [==============================] - 0s 15ms/step - loss: 0.1630 - mse: 191.6191 - val_loss: 0.2400 - val_mse: 188.1816
Epoch 88/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1656 - mse: 186.1528
10/18 [===============>..............] - ETA: 0s - loss: 0.1584 - mse: 190.2935
18/18 [==============================] - 0s 6ms/step - loss: 0.1586 - mse: 191.6192

18/18 [==============================] - 0s 14ms/step - loss: 0.1586 - mse: 191.6192 - val_loss: 0.2940 - val_mse: 188.1817
Epoch 89/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1363 - mse: 189.7190
10/18 [===============>..............] - ETA: 0s - loss: 0.1507 - mse: 190.1281
18/18 [==============================] - 0s 6ms/step - loss: 0.1557 - mse: 191.6192

18/18 [==============================] - 0s 15ms/step - loss: 0.1557 - mse: 191.6192 - val_loss: 0.2590 - val_mse: 188.1817
Epoch 90/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1609 - mse: 198.4275
10/18 [===============>..............] - ETA: 0s - loss: 0.1502 - mse: 191.0086
18/18 [==============================] - 0s 6ms/step - loss: 0.1544 - mse: 191.6192

18/18 [==============================] - 0s 15ms/step - loss: 0.1544 - mse: 191.6192 - val_loss: 0.2770 - val_mse: 188.1817
Epoch 91/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1477 - mse: 184.7753
10/18 [===============>..............] - ETA: 0s - loss: 0.1479 - mse: 191.6171
18/18 [==============================] - 0s 6ms/step - loss: 0.1494 - mse: 191.6192

18/18 [==============================] - 0s 15ms/step - loss: 0.1494 - mse: 191.6192 - val_loss: 0.2841 - val_mse: 188.1817
Epoch 92/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1549 - mse: 187.5420
10/18 [===============>..............] - ETA: 0s - loss: 0.1434 - mse: 189.4512
18/18 [==============================] - 0s 6ms/step - loss: 0.1489 - mse: 191.6193

18/18 [==============================] - 0s 15ms/step - loss: 0.1489 - mse: 191.6193 - val_loss: 0.2392 - val_mse: 188.1817
Epoch 93/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1480 - mse: 188.1170
10/18 [===============>..............] - ETA: 0s - loss: 0.1438 - mse: 189.3160
18/18 [==============================] - 0s 6ms/step - loss: 0.1463 - mse: 191.6193

18/18 [==============================] - 0s 14ms/step - loss: 0.1463 - mse: 191.6193 - val_loss: 0.2436 - val_mse: 188.1817
Epoch 94/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1544 - mse: 194.1946
10/18 [===============>..............] - ETA: 0s - loss: 0.1489 - mse: 194.0856
18/18 [==============================] - 0s 6ms/step - loss: 0.1439 - mse: 191.6193

18/18 [==============================] - 0s 15ms/step - loss: 0.1439 - mse: 191.6193 - val_loss: 0.2922 - val_mse: 188.1818
Epoch 95/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1307 - mse: 185.5005
10/18 [===============>..............] - ETA: 0s - loss: 0.1362 - mse: 188.0099
18/18 [==============================] - 0s 6ms/step - loss: 0.1402 - mse: 191.6193

18/18 [==============================] - 0s 15ms/step - loss: 0.1402 - mse: 191.6193 - val_loss: 0.2532 - val_mse: 188.1818
Epoch 96/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1328 - mse: 187.9631
10/18 [===============>..............] - ETA: 0s - loss: 0.1383 - mse: 189.7361
18/18 [==============================] - 0s 6ms/step - loss: 0.1402 - mse: 191.6193

18/18 [==============================] - 0s 14ms/step - loss: 0.1402 - mse: 191.6193 - val_loss: 0.2485 - val_mse: 188.1818
Epoch 97/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1377 - mse: 193.9805
10/18 [===============>..............] - ETA: 0s - loss: 0.1344 - mse: 192.4117
18/18 [==============================] - 0s 6ms/step - loss: 0.1355 - mse: 191.6194

18/18 [==============================] - 0s 15ms/step - loss: 0.1355 - mse: 191.6194 - val_loss: 0.3088 - val_mse: 188.1818
Epoch 98/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1460 - mse: 197.3733
 7/18 [==========>...................] - ETA: 0s - loss: 0.1399 - mse: 195.1673
15/18 [========================>.....] - ETA: 0s - loss: 0.1380 - mse: 193.8991
18/18 [==============================] - 0s 7ms/step - loss: 0.1352 - mse: 191.6194

18/18 [==============================] - 0s 17ms/step - loss: 0.1352 - mse: 191.6194 - val_loss: 0.2673 - val_mse: 188.1818
Epoch 99/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1351 - mse: 191.3754
10/18 [===============>..............] - ETA: 0s - loss: 0.1327 - mse: 190.1522
18/18 [==============================] - 0s 6ms/step - loss: 0.1348 - mse: 191.6194

18/18 [==============================] - 0s 15ms/step - loss: 0.1348 - mse: 191.6194 - val_loss: 0.2338 - val_mse: 188.1819
Epoch 100/100

 1/18 [>.............................] - ETA: 0s - loss: 0.1118 - mse: 178.6524
10/18 [===============>..............] - ETA: 0s - loss: 0.1311 - mse: 190.9818
18/18 [==============================] - 0s 6ms/step - loss: 0.1328 - mse: 191.6194

18/18 [==============================] - 0s 15ms/step - loss: 0.1328 - mse: 191.6194 - val_loss: 0.2782 - val_mse: 188.1819

Run completed: runs/2023-04-03T22-31-36Z

Training run 2/9 (flags = list(128, 0.01, 1000, 30, "tanh")) 
Using run directory runs/2023-04-03T22-32-04Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 106) %>%
+   layer_dense(units = FLAGS$nodes, activation .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('mse')
+  .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   second_bikes_matrix, second_bikes_train_set$count, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(a .... [TRUNCATED] 
Epoch 1/30

1/9 [==>...........................] - ETA: 2s - loss: 4.8282 - mse: 198.0937
7/9 [======================>.......] - ETA: 0s - loss: 4.3653 - mse: 191.4402
9/9 [==============================] - 0s 9ms/step - loss: 4.2515 - mse: 191.6115

9/9 [==============================] - 1s 88ms/step - loss: 4.2515 - mse: 191.6115 - val_loss: 3.6630 - val_mse: 188.1743
Epoch 2/30

1/9 [==>...........................] - ETA: 0s - loss: 3.6428 - mse: 184.6058
7/9 [======================>.......] - ETA: 0s - loss: 3.4620 - mse: 189.9210
9/9 [==============================] - 0s 8ms/step - loss: 3.4159 - mse: 191.6116

9/9 [==============================] - 0s 28ms/step - loss: 3.4159 - mse: 191.6116 - val_loss: 3.1478 - val_mse: 188.1744
Epoch 3/30

1/9 [==>...........................] - ETA: 0s - loss: 3.1605 - mse: 191.9244
8/9 [=========================>....] - ETA: 0s - loss: 3.0186 - mse: 191.5534
9/9 [==============================] - 0s 8ms/step - loss: 3.0065 - mse: 191.6117

9/9 [==============================] - 0s 28ms/step - loss: 3.0065 - mse: 191.6117 - val_loss: 2.8303 - val_mse: 188.1746
Epoch 4/30

1/9 [==>...........................] - ETA: 0s - loss: 2.8423 - mse: 195.2505
7/9 [======================>.......] - ETA: 0s - loss: 2.7564 - mse: 192.0219
9/9 [==============================] - 0s 9ms/step - loss: 2.7347 - mse: 191.6119

9/9 [==============================] - 0s 28ms/step - loss: 2.7347 - mse: 191.6119 - val_loss: 2.6112 - val_mse: 188.1748
Epoch 5/30

1/9 [==>...........................] - ETA: 0s - loss: 2.5912 - mse: 187.8981
7/9 [======================>.......] - ETA: 0s - loss: 2.5462 - mse: 190.6662
9/9 [==============================] - 0s 8ms/step - loss: 2.5308 - mse: 191.6120

9/9 [==============================] - 0s 28ms/step - loss: 2.5308 - mse: 191.6120 - val_loss: 2.4494 - val_mse: 188.1749
Epoch 6/30

1/9 [==>...........................] - ETA: 0s - loss: 2.4485 - mse: 193.2118
7/9 [======================>.......] - ETA: 0s - loss: 2.3833 - mse: 191.2220
9/9 [==============================] - 0s 8ms/step - loss: 2.3714 - mse: 191.6122

9/9 [==============================] - 0s 29ms/step - loss: 2.3714 - mse: 191.6122 - val_loss: 2.3199 - val_mse: 188.1750
Epoch 7/30

1/9 [==>...........................] - ETA: 0s - loss: 2.2949 - mse: 193.0358
7/9 [======================>.......] - ETA: 0s - loss: 2.2513 - mse: 192.0004
9/9 [==============================] - 0s 8ms/step - loss: 2.2401 - mse: 191.6123

9/9 [==============================] - 0s 28ms/step - loss: 2.2401 - mse: 191.6123 - val_loss: 2.2045 - val_mse: 188.1752
Epoch 8/30

1/9 [==>...........................] - ETA: 0s - loss: 2.1608 - mse: 191.4462
7/9 [======================>.......] - ETA: 0s - loss: 2.1429 - mse: 191.8837
9/9 [==============================] - 0s 8ms/step - loss: 2.1300 - mse: 191.6124

9/9 [==============================] - 0s 27ms/step - loss: 2.1300 - mse: 191.6124 - val_loss: 2.1291 - val_mse: 188.1753
Epoch 9/30

1/9 [==>...........................] - ETA: 0s - loss: 2.0708 - mse: 189.9402
7/9 [======================>.......] - ETA: 0s - loss: 2.0395 - mse: 190.8006
9/9 [==============================] - 0s 8ms/step - loss: 2.0347 - mse: 191.6125

9/9 [==============================] - 0s 27ms/step - loss: 2.0347 - mse: 191.6125 - val_loss: 2.0335 - val_mse: 188.1754
Epoch 10/30

1/9 [==>...........................] - ETA: 0s - loss: 2.0266 - mse: 198.4220
7/9 [======================>.......] - ETA: 0s - loss: 1.9587 - mse: 190.4531
9/9 [==============================] - 0s 8ms/step - loss: 1.9521 - mse: 191.6126

9/9 [==============================] - 0s 28ms/step - loss: 1.9521 - mse: 191.6126 - val_loss: 1.9511 - val_mse: 188.1754
Epoch 11/30

1/9 [==>...........................] - ETA: 0s - loss: 1.8801 - mse: 183.6333
7/9 [======================>.......] - ETA: 0s - loss: 1.8776 - mse: 189.6246
9/9 [==============================] - 0s 9ms/step - loss: 1.8759 - mse: 191.6126

9/9 [==============================] - 0s 29ms/step - loss: 1.8759 - mse: 191.6126 - val_loss: 1.8887 - val_mse: 188.1755
Epoch 12/30

1/9 [==>...........................] - ETA: 0s - loss: 1.8418 - mse: 194.2772
7/9 [======================>.......] - ETA: 0s - loss: 1.8165 - mse: 192.6463
9/9 [==============================] - 0s 8ms/step - loss: 1.8062 - mse: 191.6127

9/9 [==============================] - 0s 29ms/step - loss: 1.8062 - mse: 191.6127 - val_loss: 1.8150 - val_mse: 188.1756
Epoch 13/30

1/9 [==>...........................] - ETA: 0s - loss: 1.7875 - mse: 195.7442
8/9 [=========================>....] - ETA: 0s - loss: 1.7443 - mse: 191.0575
9/9 [==============================] - 0s 8ms/step - loss: 1.7421 - mse: 191.6128

9/9 [==============================] - 0s 26ms/step - loss: 1.7421 - mse: 191.6128 - val_loss: 1.7511 - val_mse: 188.1757
Epoch 14/30

1/9 [==>...........................] - ETA: 0s - loss: 1.7306 - mse: 196.3147
7/9 [======================>.......] - ETA: 0s - loss: 1.6883 - mse: 192.3128
9/9 [==============================] - 0s 8ms/step - loss: 1.6808 - mse: 191.6129

9/9 [==============================] - 0s 26ms/step - loss: 1.6808 - mse: 191.6129 - val_loss: 1.6893 - val_mse: 188.1758
Epoch 15/30

1/9 [==>...........................] - ETA: 0s - loss: 1.6221 - mse: 185.7209
7/9 [======================>.......] - ETA: 0s - loss: 1.6342 - mse: 193.4931
9/9 [==============================] - 0s 8ms/step - loss: 1.6229 - mse: 191.6130

9/9 [==============================] - 0s 28ms/step - loss: 1.6229 - mse: 191.6130 - val_loss: 1.6322 - val_mse: 188.1758
Epoch 16/30

1/9 [==>...........................] - ETA: 0s - loss: 1.5815 - mse: 190.3067
7/9 [======================>.......] - ETA: 0s - loss: 1.5726 - mse: 191.7025
9/9 [==============================] - 0s 8ms/step - loss: 1.5661 - mse: 191.6131

9/9 [==============================] - 0s 27ms/step - loss: 1.5661 - mse: 191.6131 - val_loss: 1.5699 - val_mse: 188.1759
Epoch 17/30

1/9 [==>...........................] - ETA: 0s - loss: 1.5271 - mse: 191.7789
8/9 [=========================>....] - ETA: 0s - loss: 1.5122 - mse: 191.3054
9/9 [==============================] - 0s 8ms/step - loss: 1.5122 - mse: 191.6132

9/9 [==============================] - 0s 26ms/step - loss: 1.5122 - mse: 191.6132 - val_loss: 1.5177 - val_mse: 188.1760
Epoch 18/30

1/9 [==>...........................] - ETA: 0s - loss: 1.4934 - mse: 197.4048
7/9 [======================>.......] - ETA: 0s - loss: 1.4662 - mse: 191.8450
9/9 [==============================] - 0s 8ms/step - loss: 1.4613 - mse: 191.6132

9/9 [==============================] - 0s 27ms/step - loss: 1.4613 - mse: 191.6132 - val_loss: 1.4618 - val_mse: 188.1761
Epoch 19/30

1/9 [==>...........................] - ETA: 0s - loss: 1.4135 - mse: 186.7894
7/9 [======================>.......] - ETA: 0s - loss: 1.4162 - mse: 191.5877
9/9 [==============================] - 0s 8ms/step - loss: 1.4130 - mse: 191.6133

9/9 [==============================] - 0s 26ms/step - loss: 1.4130 - mse: 191.6133 - val_loss: 1.4215 - val_mse: 188.1762
Epoch 20/30

1/9 [==>...........................] - ETA: 0s - loss: 1.3814 - mse: 189.7183
7/9 [======================>.......] - ETA: 0s - loss: 1.3751 - mse: 193.0648
9/9 [==============================] - 0s 8ms/step - loss: 1.3661 - mse: 191.6134

9/9 [==============================] - 0s 28ms/step - loss: 1.3661 - mse: 191.6134 - val_loss: 1.3685 - val_mse: 188.1763
Epoch 21/30

1/9 [==>...........................] - ETA: 0s - loss: 1.3346 - mse: 189.6787
8/9 [=========================>....] - ETA: 0s - loss: 1.3246 - mse: 192.1902
9/9 [==============================] - 0s 8ms/step - loss: 1.3223 - mse: 191.6135

9/9 [==============================] - 0s 28ms/step - loss: 1.3223 - mse: 191.6135 - val_loss: 1.3283 - val_mse: 188.1763
Epoch 22/30

1/9 [==>...........................] - ETA: 0s - loss: 1.2789 - mse: 189.7781
7/9 [======================>.......] - ETA: 0s - loss: 1.2846 - mse: 191.6616
9/9 [==============================] - 0s 8ms/step - loss: 1.2817 - mse: 191.6136

9/9 [==============================] - 0s 30ms/step - loss: 1.2817 - mse: 191.6136 - val_loss: 1.2898 - val_mse: 188.1764
Epoch 23/30

1/9 [==>...........................] - ETA: 0s - loss: 1.2659 - mse: 193.6857
7/9 [======================>.......] - ETA: 0s - loss: 1.2394 - mse: 190.4719
9/9 [==============================] - 0s 8ms/step - loss: 1.2407 - mse: 191.6136

9/9 [==============================] - 0s 28ms/step - loss: 1.2407 - mse: 191.6136 - val_loss: 1.2504 - val_mse: 188.1765
Epoch 24/30

1/9 [==>...........................] - ETA: 0s - loss: 1.2381 - mse: 196.2240
7/9 [======================>.......] - ETA: 0s - loss: 1.2075 - mse: 191.4634
9/9 [==============================] - 0s 8ms/step - loss: 1.2016 - mse: 191.6137

9/9 [==============================] - 0s 29ms/step - loss: 1.2016 - mse: 191.6137 - val_loss: 1.2089 - val_mse: 188.1766
Epoch 25/30

1/9 [==>...........................] - ETA: 0s - loss: 1.1449 - mse: 182.8246
7/9 [======================>.......] - ETA: 0s - loss: 1.1673 - mse: 192.0141
9/9 [==============================] - 0s 8ms/step - loss: 1.1661 - mse: 191.6138

9/9 [==============================] - 0s 27ms/step - loss: 1.1661 - mse: 191.6138 - val_loss: 1.1664 - val_mse: 188.1767
Epoch 26/30

1/9 [==>...........................] - ETA: 0s - loss: 1.1494 - mse: 192.6406
7/9 [======================>.......] - ETA: 0s - loss: 1.1296 - mse: 190.6833
9/9 [==============================] - 0s 8ms/step - loss: 1.1299 - mse: 191.6139

9/9 [==============================] - 0s 28ms/step - loss: 1.1299 - mse: 191.6139 - val_loss: 1.1433 - val_mse: 188.1768
Epoch 27/30

1/9 [==>...........................] - ETA: 0s - loss: 1.1342 - mse: 196.5912
7/9 [======================>.......] - ETA: 0s - loss: 1.1008 - mse: 192.9359
9/9 [==============================] - 0s 8ms/step - loss: 1.0958 - mse: 191.6140

9/9 [==============================] - 0s 28ms/step - loss: 1.0958 - mse: 191.6140 - val_loss: 1.1042 - val_mse: 188.1768
Epoch 28/30

1/9 [==>...........................] - ETA: 0s - loss: 1.0760 - mse: 190.4616
7/9 [======================>.......] - ETA: 0s - loss: 1.0679 - mse: 191.7028
9/9 [==============================] - 0s 8ms/step - loss: 1.0660 - mse: 191.6141

9/9 [==============================] - 0s 28ms/step - loss: 1.0660 - mse: 191.6141 - val_loss: 1.0743 - val_mse: 188.1769
Epoch 29/30

1/9 [==>...........................] - ETA: 0s - loss: 1.0226 - mse: 184.3821
7/9 [======================>.......] - ETA: 0s - loss: 1.0325 - mse: 189.9548
9/9 [==============================] - 0s 8ms/step - loss: 1.0340 - mse: 191.6142

9/9 [==============================] - 0s 29ms/step - loss: 1.0340 - mse: 191.6142 - val_loss: 1.0539 - val_mse: 188.1770
Epoch 30/30

1/9 [==>...........................] - ETA: 0s - loss: 1.0210 - mse: 193.3969
6/9 [===================>..........] - ETA: 0s - loss: 0.9989 - mse: 188.3823
9/9 [==============================] - 0s 10ms/step - loss: 1.0049 - mse: 191.6143

9/9 [==============================] - 0s 29ms/step - loss: 1.0049 - mse: 191.6143 - val_loss: 1.0165 - val_mse: 188.1771

Run completed: runs/2023-04-03T22-32-04Z

Training run 3/9 (flags = list(392, 0.05, 1000, 30, "tanh")) 
Using run directory runs/2023-04-03T22-32-12Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 106) %>%
+   layer_dense(units = FLAGS$nodes, activation .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('mse')
+  .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   second_bikes_matrix, second_bikes_train_set$count, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(a .... [TRUNCATED] 
Epoch 1/30

1/9 [==>...........................] - ETA: 2s - loss: 4.8439 - mse: 198.4552
6/9 [===================>..........] - ETA: 0s - loss: 3.7755 - mse: 190.6944
9/9 [==============================] - 0s 11ms/step - loss: 3.5345 - mse: 191.6116

9/9 [==============================] - 1s 92ms/step - loss: 3.5345 - mse: 191.6116 - val_loss: 2.8986 - val_mse: 188.1747
Epoch 2/30

1/9 [==>...........................] - ETA: 0s - loss: 2.8942 - mse: 189.4493
6/9 [===================>..........] - ETA: 0s - loss: 2.7687 - mse: 193.0983
9/9 [==============================] - 0s 12ms/step - loss: 2.7020 - mse: 191.6120

9/9 [==============================] - 0s 32ms/step - loss: 2.7020 - mse: 191.6120 - val_loss: 2.4897 - val_mse: 188.1750
Epoch 3/30

1/9 [==>...........................] - ETA: 0s - loss: 2.4929 - mse: 188.3148
6/9 [===================>..........] - ETA: 0s - loss: 2.4151 - mse: 189.4912
9/9 [==============================] - 0s 12ms/step - loss: 2.3833 - mse: 191.6123

9/9 [==============================] - 0s 30ms/step - loss: 2.3833 - mse: 191.6123 - val_loss: 2.2446 - val_mse: 188.1752
Epoch 4/30

1/9 [==>...........................] - ETA: 0s - loss: 2.2222 - mse: 191.3074
6/9 [===================>..........] - ETA: 0s - loss: 2.1850 - mse: 193.0679
9/9 [==============================] - 0s 12ms/step - loss: 2.1500 - mse: 191.6125

9/9 [==============================] - 0s 30ms/step - loss: 2.1500 - mse: 191.6125 - val_loss: 2.1309 - val_mse: 188.1754
Epoch 5/30

1/9 [==>...........................] - ETA: 0s - loss: 2.0576 - mse: 195.3570
6/9 [===================>..........] - ETA: 0s - loss: 1.9909 - mse: 191.6526
9/9 [==============================] - 0s 11ms/step - loss: 1.9649 - mse: 191.6126

9/9 [==============================] - 0s 30ms/step - loss: 1.9649 - mse: 191.6126 - val_loss: 1.9580 - val_mse: 188.1756
Epoch 6/30

1/9 [==>...........................] - ETA: 0s - loss: 1.8956 - mse: 200.8068
6/9 [===================>..........] - ETA: 0s - loss: 1.8273 - mse: 190.4919
9/9 [==============================] - 0s 12ms/step - loss: 1.8085 - mse: 191.6128

9/9 [==============================] - 0s 32ms/step - loss: 1.8085 - mse: 191.6128 - val_loss: 1.8156 - val_mse: 188.1757
Epoch 7/30

1/9 [==>...........................] - ETA: 0s - loss: 1.7082 - mse: 188.1308
6/9 [===================>..........] - ETA: 0s - loss: 1.6961 - mse: 190.5406
9/9 [==============================] - 0s 11ms/step - loss: 1.6804 - mse: 191.6130

9/9 [==============================] - 0s 30ms/step - loss: 1.6804 - mse: 191.6130 - val_loss: 1.6818 - val_mse: 188.1759
Epoch 8/30

1/9 [==>...........................] - ETA: 0s - loss: 1.6090 - mse: 193.1862
6/9 [===================>..........] - ETA: 0s - loss: 1.5969 - mse: 193.6648
9/9 [==============================] - 0s 11ms/step - loss: 1.5701 - mse: 191.6131

9/9 [==============================] - 0s 30ms/step - loss: 1.5701 - mse: 191.6131 - val_loss: 1.5922 - val_mse: 188.1760
Epoch 9/30

1/9 [==>...........................] - ETA: 0s - loss: 1.4862 - mse: 182.9732
6/9 [===================>..........] - ETA: 0s - loss: 1.4823 - mse: 191.0075
9/9 [==============================] - 0s 11ms/step - loss: 1.4709 - mse: 191.6133

9/9 [==============================] - 0s 30ms/step - loss: 1.4709 - mse: 191.6133 - val_loss: 1.4866 - val_mse: 188.1761
Epoch 10/30

1/9 [==>...........................] - ETA: 0s - loss: 1.4133 - mse: 193.1374
6/9 [===================>..........] - ETA: 0s - loss: 1.3958 - mse: 192.1321
9/9 [==============================] - 0s 12ms/step - loss: 1.3814 - mse: 191.6134

9/9 [==============================] - 0s 31ms/step - loss: 1.3814 - mse: 191.6134 - val_loss: 1.3820 - val_mse: 188.1763
Epoch 11/30

1/9 [==>...........................] - ETA: 0s - loss: 1.3334 - mse: 187.6446
6/9 [===================>..........] - ETA: 0s - loss: 1.3135 - mse: 192.6561
9/9 [==============================] - 0s 12ms/step - loss: 1.2995 - mse: 191.6136

9/9 [==============================] - 0s 30ms/step - loss: 1.2995 - mse: 191.6136 - val_loss: 1.2971 - val_mse: 188.1764
Epoch 12/30

1/9 [==>...........................] - ETA: 0s - loss: 1.2105 - mse: 182.6014
6/9 [===================>..........] - ETA: 0s - loss: 1.2316 - mse: 190.9720
9/9 [==============================] - 0s 12ms/step - loss: 1.2248 - mse: 191.6138

9/9 [==============================] - 0s 30ms/step - loss: 1.2248 - mse: 191.6138 - val_loss: 1.2303 - val_mse: 188.1766
Epoch 13/30

1/9 [==>...........................] - ETA: 0s - loss: 1.1653 - mse: 186.2849
6/9 [===================>..........] - ETA: 0s - loss: 1.1710 - mse: 192.3533
9/9 [==============================] - 0s 12ms/step - loss: 1.1589 - mse: 191.6140

9/9 [==============================] - 0s 30ms/step - loss: 1.1589 - mse: 191.6140 - val_loss: 1.1600 - val_mse: 188.1767
Epoch 14/30

1/9 [==>...........................] - ETA: 0s - loss: 1.1022 - mse: 186.5651
6/9 [===================>..........] - ETA: 0s - loss: 1.0963 - mse: 189.4853
9/9 [==============================] - 0s 12ms/step - loss: 1.0969 - mse: 191.6141

9/9 [==============================] - 0s 32ms/step - loss: 1.0969 - mse: 191.6141 - val_loss: 1.0961 - val_mse: 188.1769
Epoch 15/30

1/9 [==>...........................] - ETA: 0s - loss: 1.0684 - mse: 192.3257
6/9 [===================>..........] - ETA: 0s - loss: 1.0486 - mse: 192.8013
9/9 [==============================] - 0s 11ms/step - loss: 1.0396 - mse: 191.6142

9/9 [==============================] - 0s 30ms/step - loss: 1.0396 - mse: 191.6142 - val_loss: 1.0417 - val_mse: 188.1770
Epoch 16/30

1/9 [==>...........................] - ETA: 0s - loss: 1.0142 - mse: 194.5668
6/9 [===================>..........] - ETA: 0s - loss: 0.9911 - mse: 191.2686
9/9 [==============================] - 0s 12ms/step - loss: 0.9836 - mse: 191.6144

9/9 [==============================] - 0s 32ms/step - loss: 0.9836 - mse: 191.6144 - val_loss: 0.9998 - val_mse: 188.1772
Epoch 17/30

1/9 [==>...........................] - ETA: 0s - loss: 0.9555 - mse: 193.4483
6/9 [===================>..........] - ETA: 0s - loss: 0.9419 - mse: 192.3127
9/9 [==============================] - 0s 11ms/step - loss: 0.9333 - mse: 191.6145

9/9 [==============================] - 0s 30ms/step - loss: 0.9333 - mse: 191.6145 - val_loss: 0.9410 - val_mse: 188.1774
Epoch 18/30

1/9 [==>...........................] - ETA: 0s - loss: 0.9022 - mse: 192.4990
6/9 [===================>..........] - ETA: 0s - loss: 0.8950 - mse: 190.8623
9/9 [==============================] - 0s 12ms/step - loss: 0.8905 - mse: 191.6147

9/9 [==============================] - 0s 31ms/step - loss: 0.8905 - mse: 191.6147 - val_loss: 0.8970 - val_mse: 188.1775
Epoch 19/30

1/9 [==>...........................] - ETA: 0s - loss: 0.8498 - mse: 188.6414
6/9 [===================>..........] - ETA: 0s - loss: 0.8573 - mse: 192.6852
9/9 [==============================] - 0s 12ms/step - loss: 0.8470 - mse: 191.6149

9/9 [==============================] - 0s 31ms/step - loss: 0.8470 - mse: 191.6149 - val_loss: 0.8779 - val_mse: 188.1777
Epoch 20/30

1/9 [==>...........................] - ETA: 0s - loss: 0.8107 - mse: 185.2397
6/9 [===================>..........] - ETA: 0s - loss: 0.8123 - mse: 191.7402
9/9 [==============================] - 0s 12ms/step - loss: 0.8069 - mse: 191.6150

9/9 [==============================] - 0s 32ms/step - loss: 0.8069 - mse: 191.6150 - val_loss: 0.8301 - val_mse: 188.1778
Epoch 21/30

1/9 [==>...........................] - ETA: 0s - loss: 0.7840 - mse: 193.7986
6/9 [===================>..........] - ETA: 0s - loss: 0.7722 - mse: 191.6238
9/9 [==============================] - 0s 12ms/step - loss: 0.7662 - mse: 191.6152

9/9 [==============================] - 0s 32ms/step - loss: 0.7662 - mse: 191.6152 - val_loss: 0.7855 - val_mse: 188.1780
Epoch 22/30

1/9 [==>...........................] - ETA: 0s - loss: 0.7467 - mse: 194.6207
5/9 [===============>..............] - ETA: 0s - loss: 0.7452 - mse: 193.0981
9/9 [==============================] - 0s 12ms/step - loss: 0.7357 - mse: 191.6153

9/9 [==============================] - 0s 33ms/step - loss: 0.7357 - mse: 191.6153 - val_loss: 0.7678 - val_mse: 188.1782
Epoch 23/30

1/9 [==>...........................] - ETA: 0s - loss: 0.7262 - mse: 195.4693
5/9 [===============>..............] - ETA: 0s - loss: 0.7099 - mse: 190.0087
9/9 [==============================] - 0s 13ms/step - loss: 0.7052 - mse: 191.6155

9/9 [==============================] - 0s 32ms/step - loss: 0.7052 - mse: 191.6155 - val_loss: 0.7304 - val_mse: 188.1783
Epoch 24/30

1/9 [==>...........................] - ETA: 0s - loss: 0.6863 - mse: 186.5750
6/9 [===================>..........] - ETA: 0s - loss: 0.6756 - mse: 190.7478
9/9 [==============================] - 0s 12ms/step - loss: 0.6741 - mse: 191.6156

9/9 [==============================] - 0s 32ms/step - loss: 0.6741 - mse: 191.6156 - val_loss: 0.6999 - val_mse: 188.1784
Epoch 25/30

1/9 [==>...........................] - ETA: 0s - loss: 0.6690 - mse: 192.6693
5/9 [===============>..............] - ETA: 0s - loss: 0.6544 - mse: 194.3317
9/9 [==============================] - 0s 13ms/step - loss: 0.6436 - mse: 191.6158

9/9 [==============================] - 0s 32ms/step - loss: 0.6436 - mse: 191.6158 - val_loss: 0.6711 - val_mse: 188.1785
Epoch 26/30

1/9 [==>...........................] - ETA: 0s - loss: 0.6169 - mse: 189.3377
6/9 [===================>..........] - ETA: 0s - loss: 0.6209 - mse: 192.6167
9/9 [==============================] - 0s 12ms/step - loss: 0.6162 - mse: 191.6159

9/9 [==============================] - 0s 30ms/step - loss: 0.6162 - mse: 191.6159 - val_loss: 0.6388 - val_mse: 188.1787
Epoch 27/30

1/9 [==>...........................] - ETA: 0s - loss: 0.6168 - mse: 194.0064
6/9 [===================>..........] - ETA: 0s - loss: 0.5984 - mse: 191.9264
9/9 [==============================] - 0s 12ms/step - loss: 0.5940 - mse: 191.6160

9/9 [==============================] - 0s 30ms/step - loss: 0.5940 - mse: 191.6160 - val_loss: 0.6215 - val_mse: 188.1787
Epoch 28/30

1/9 [==>...........................] - ETA: 0s - loss: 0.5777 - mse: 187.1830
6/9 [===================>..........] - ETA: 0s - loss: 0.5793 - mse: 194.5662
9/9 [==============================] - 0s 12ms/step - loss: 0.5686 - mse: 191.6161

9/9 [==============================] - 0s 30ms/step - loss: 0.5686 - mse: 191.6161 - val_loss: 0.6034 - val_mse: 188.1789
Epoch 29/30

1/9 [==>...........................] - ETA: 0s - loss: 0.5529 - mse: 190.0781
6/9 [===================>..........] - ETA: 0s - loss: 0.5466 - mse: 190.1476
9/9 [==============================] - 0s 12ms/step - loss: 0.5482 - mse: 191.6163

9/9 [==============================] - 0s 31ms/step - loss: 0.5482 - mse: 191.6163 - val_loss: 0.5870 - val_mse: 188.1790
Epoch 30/30

1/9 [==>...........................] - ETA: 0s - loss: 0.5296 - mse: 188.0982
4/9 [============>.................] - ETA: 0s - loss: 0.5301 - mse: 191.2200
8/9 [=========================>....] - ETA: 0s - loss: 0.5292 - mse: 191.3770
9/9 [==============================] - 0s 15ms/step - loss: 0.5290 - mse: 191.6164

9/9 [==============================] - 0s 36ms/step - loss: 0.5290 - mse: 191.6164 - val_loss: 0.5712 - val_mse: 188.1791

Run completed: runs/2023-04-03T22-32-12Z

Training run 4/9 (flags = list(392, 0.05, 1000, 30, "relu")) 
Using run directory runs/2023-04-03T22-32-21Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 106) %>%
+   layer_dense(units = FLAGS$nodes, activation .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('mse')
+  .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   second_bikes_matrix, second_bikes_train_set$count, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(a .... [TRUNCATED] 
Epoch 1/30

1/9 [==>...........................] - ETA: 3s - loss: 4.7681 - mse: 199.2224
6/9 [===================>..........] - ETA: 0s - loss: 3.9773 - mse: 191.5173
9/9 [==============================] - 0s 11ms/step - loss: 3.7712 - mse: 191.6116

9/9 [==============================] - 1s 93ms/step - loss: 3.7712 - mse: 191.6116 - val_loss: 3.1995 - val_mse: 188.1745
Epoch 2/30

1/9 [==>...........................] - ETA: 0s - loss: 3.1378 - mse: 196.1520
6/9 [===================>..........] - ETA: 0s - loss: 2.9933 - mse: 191.6806
9/9 [==============================] - 0s 12ms/step - loss: 2.9172 - mse: 191.6118

9/9 [==============================] - 0s 32ms/step - loss: 2.9172 - mse: 191.6118 - val_loss: 2.6871 - val_mse: 188.1748
Epoch 3/30

1/9 [==>...........................] - ETA: 0s - loss: 2.6497 - mse: 195.0451
6/9 [===================>..........] - ETA: 0s - loss: 2.5407 - mse: 191.1338
9/9 [==============================] - 0s 11ms/step - loss: 2.4902 - mse: 191.6122

9/9 [==============================] - 0s 34ms/step - loss: 2.4902 - mse: 191.6122 - val_loss: 2.3605 - val_mse: 188.1752
Epoch 4/30

1/9 [==>...........................] - ETA: 0s - loss: 2.3037 - mse: 193.4640
6/9 [===================>..........] - ETA: 0s - loss: 2.2169 - mse: 191.5958
9/9 [==============================] - 0s 12ms/step - loss: 2.1785 - mse: 191.6125

9/9 [==============================] - 0s 32ms/step - loss: 2.1785 - mse: 191.6125 - val_loss: 2.1251 - val_mse: 188.1755
Epoch 5/30

1/9 [==>...........................] - ETA: 0s - loss: 2.0460 - mse: 193.4949
6/9 [===================>..........] - ETA: 0s - loss: 1.9703 - mse: 193.2105
9/9 [==============================] - 0s 12ms/step - loss: 1.9339 - mse: 191.6127

9/9 [==============================] - 0s 32ms/step - loss: 1.9339 - mse: 191.6127 - val_loss: 1.9313 - val_mse: 188.1757
Epoch 6/30

1/9 [==>...........................] - ETA: 0s - loss: 1.7857 - mse: 191.3386
6/9 [===================>..........] - ETA: 0s - loss: 1.7673 - mse: 191.0009
9/9 [==============================] - 0s 12ms/step - loss: 1.7458 - mse: 191.6130

9/9 [==============================] - 0s 32ms/step - loss: 1.7458 - mse: 191.6130 - val_loss: 1.7446 - val_mse: 188.1760
Epoch 7/30

1/9 [==>...........................] - ETA: 0s - loss: 1.6267 - mse: 184.1364
6/9 [===================>..........] - ETA: 0s - loss: 1.6090 - mse: 190.9971
9/9 [==============================] - 0s 12ms/step - loss: 1.5888 - mse: 191.6133

9/9 [==============================] - 0s 32ms/step - loss: 1.5888 - mse: 191.6133 - val_loss: 1.6131 - val_mse: 188.1761
Epoch 8/30

1/9 [==>...........................] - ETA: 0s - loss: 1.4928 - mse: 190.5797
6/9 [===================>..........] - ETA: 0s - loss: 1.4745 - mse: 191.9778
9/9 [==============================] - 0s 12ms/step - loss: 1.4558 - mse: 191.6134

9/9 [==============================] - 0s 31ms/step - loss: 1.4558 - mse: 191.6134 - val_loss: 1.5173 - val_mse: 188.1765
Epoch 9/30

1/9 [==>...........................] - ETA: 0s - loss: 1.3519 - mse: 181.4126
6/9 [===================>..........] - ETA: 0s - loss: 1.3564 - mse: 188.2845
9/9 [==============================] - 0s 12ms/step - loss: 1.3493 - mse: 191.6137

9/9 [==============================] - 0s 30ms/step - loss: 1.3493 - mse: 191.6137 - val_loss: 1.3899 - val_mse: 188.1766
Epoch 10/30

1/9 [==>...........................] - ETA: 0s - loss: 1.2757 - mse: 187.6374
5/9 [===============>..............] - ETA: 0s - loss: 1.2664 - mse: 192.1682
9/9 [==============================] - 0s 13ms/step - loss: 1.2581 - mse: 191.6138

9/9 [==============================] - 0s 34ms/step - loss: 1.2581 - mse: 191.6138 - val_loss: 1.3180 - val_mse: 188.1768
Epoch 11/30

1/9 [==>...........................] - ETA: 0s - loss: 1.2218 - mse: 190.9003
6/9 [===================>..........] - ETA: 0s - loss: 1.1937 - mse: 193.0271
9/9 [==============================] - 0s 12ms/step - loss: 1.1795 - mse: 191.6141

9/9 [==============================] - 0s 35ms/step - loss: 1.1795 - mse: 191.6141 - val_loss: 1.2416 - val_mse: 188.1769
Epoch 12/30

1/9 [==>...........................] - ETA: 0s - loss: 1.1445 - mse: 192.5686
5/9 [===============>..............] - ETA: 0s - loss: 1.1232 - mse: 191.1835
9/9 [==============================] - 0s 13ms/step - loss: 1.1050 - mse: 191.6142

9/9 [==============================] - 0s 34ms/step - loss: 1.1050 - mse: 191.6142 - val_loss: 1.1637 - val_mse: 188.1770
Epoch 13/30

1/9 [==>...........................] - ETA: 0s - loss: 1.0756 - mse: 189.2659
5/9 [===============>..............] - ETA: 0s - loss: 1.0435 - mse: 189.3316
9/9 [==============================] - 0s 13ms/step - loss: 1.0390 - mse: 191.6144

9/9 [==============================] - 0s 34ms/step - loss: 1.0390 - mse: 191.6144 - val_loss: 1.0943 - val_mse: 188.1773
Epoch 14/30

1/9 [==>...........................] - ETA: 0s - loss: 1.0111 - mse: 193.6024
5/9 [===============>..............] - ETA: 0s - loss: 0.9977 - mse: 190.0620
9/9 [==============================] - 0s 14ms/step - loss: 0.9906 - mse: 191.6146

9/9 [==============================] - 0s 34ms/step - loss: 0.9906 - mse: 191.6146 - val_loss: 1.0355 - val_mse: 188.1774
Epoch 15/30

1/9 [==>...........................] - ETA: 0s - loss: 0.9256 - mse: 181.5304
5/9 [===============>..............] - ETA: 0s - loss: 0.9355 - mse: 190.9578
9/9 [==============================] - 0s 12ms/step - loss: 0.9311 - mse: 191.6147

9/9 [==============================] - 0s 36ms/step - loss: 0.9311 - mse: 191.6147 - val_loss: 0.9931 - val_mse: 188.1776
Epoch 16/30

1/9 [==>...........................] - ETA: 0s - loss: 0.9047 - mse: 190.7194
6/9 [===================>..........] - ETA: 0s - loss: 0.8958 - mse: 192.7068
9/9 [==============================] - 0s 12ms/step - loss: 0.8862 - mse: 191.6149

9/9 [==============================] - 0s 30ms/step - loss: 0.8862 - mse: 191.6149 - val_loss: 0.9588 - val_mse: 188.1777
Epoch 17/30

1/9 [==>...........................] - ETA: 0s - loss: 0.8352 - mse: 191.1426
6/9 [===================>..........] - ETA: 0s - loss: 0.8423 - mse: 192.2227
9/9 [==============================] - 0s 11ms/step - loss: 0.8346 - mse: 191.6151

9/9 [==============================] - 0s 30ms/step - loss: 0.8346 - mse: 191.6151 - val_loss: 0.9005 - val_mse: 188.1779
Epoch 18/30

1/9 [==>...........................] - ETA: 0s - loss: 0.8282 - mse: 196.4086
6/9 [===================>..........] - ETA: 0s - loss: 0.8121 - mse: 194.1447
9/9 [==============================] - 0s 11ms/step - loss: 0.7998 - mse: 191.6152

9/9 [==============================] - 0s 30ms/step - loss: 0.7998 - mse: 191.6152 - val_loss: 0.8982 - val_mse: 188.1780
Epoch 19/30

1/9 [==>...........................] - ETA: 0s - loss: 0.7662 - mse: 190.4145
6/9 [===================>..........] - ETA: 0s - loss: 0.7661 - mse: 190.4750
9/9 [==============================] - 0s 12ms/step - loss: 0.7606 - mse: 191.6154

9/9 [==============================] - 0s 32ms/step - loss: 0.7606 - mse: 191.6154 - val_loss: 0.8549 - val_mse: 188.1782
Epoch 20/30

1/9 [==>...........................] - ETA: 0s - loss: 0.7307 - mse: 188.8036
6/9 [===================>..........] - ETA: 0s - loss: 0.7365 - mse: 192.1288
9/9 [==============================] - 0s 12ms/step - loss: 0.7343 - mse: 191.6155

9/9 [==============================] - 0s 30ms/step - loss: 0.7343 - mse: 191.6155 - val_loss: 0.8049 - val_mse: 188.1783
Epoch 21/30

1/9 [==>...........................] - ETA: 0s - loss: 0.7030 - mse: 186.0411
6/9 [===================>..........] - ETA: 0s - loss: 0.7052 - mse: 189.8341
9/9 [==============================] - 0s 11ms/step - loss: 0.7078 - mse: 191.6156

9/9 [==============================] - 0s 30ms/step - loss: 0.7078 - mse: 191.6156 - val_loss: 0.7964 - val_mse: 188.1784
Epoch 22/30

1/9 [==>...........................] - ETA: 0s - loss: 0.6963 - mse: 198.7149
6/9 [===================>..........] - ETA: 0s - loss: 0.6867 - mse: 192.4853
9/9 [==============================] - 0s 11ms/step - loss: 0.6844 - mse: 191.6158

9/9 [==============================] - 0s 30ms/step - loss: 0.6844 - mse: 191.6158 - val_loss: 0.7644 - val_mse: 188.1785
Epoch 23/30

1/9 [==>...........................] - ETA: 0s - loss: 0.6450 - mse: 188.3978
6/9 [===================>..........] - ETA: 0s - loss: 0.6460 - mse: 190.0218
9/9 [==============================] - 0s 11ms/step - loss: 0.6470 - mse: 191.6159

9/9 [==============================] - 0s 30ms/step - loss: 0.6470 - mse: 191.6159 - val_loss: 0.7344 - val_mse: 188.1787
Epoch 24/30

1/9 [==>...........................] - ETA: 0s - loss: 0.6267 - mse: 195.2827
6/9 [===================>..........] - ETA: 0s - loss: 0.6238 - mse: 193.5727
9/9 [==============================] - 0s 11ms/step - loss: 0.6195 - mse: 191.6160

9/9 [==============================] - 0s 30ms/step - loss: 0.6195 - mse: 191.6160 - val_loss: 0.7608 - val_mse: 188.1788
Epoch 25/30

1/9 [==>...........................] - ETA: 0s - loss: 0.6195 - mse: 188.5795
6/9 [===================>..........] - ETA: 0s - loss: 0.6106 - mse: 191.2227
9/9 [==============================] - 0s 11ms/step - loss: 0.6137 - mse: 191.6161

9/9 [==============================] - 0s 30ms/step - loss: 0.6137 - mse: 191.6161 - val_loss: 0.7003 - val_mse: 188.1790
Epoch 26/30

1/9 [==>...........................] - ETA: 0s - loss: 0.5947 - mse: 191.3642
6/9 [===================>..........] - ETA: 0s - loss: 0.5917 - mse: 191.6880
9/9 [==============================] - 0s 11ms/step - loss: 0.5851 - mse: 191.6162

9/9 [==============================] - 0s 32ms/step - loss: 0.5851 - mse: 191.6162 - val_loss: 0.6934 - val_mse: 188.1789
Epoch 27/30

1/9 [==>...........................] - ETA: 0s - loss: 0.5627 - mse: 185.9008
6/9 [===================>..........] - ETA: 0s - loss: 0.5706 - mse: 188.9460
9/9 [==============================] - 0s 11ms/step - loss: 0.5713 - mse: 191.6164

9/9 [==============================] - 0s 30ms/step - loss: 0.5713 - mse: 191.6164 - val_loss: 0.6711 - val_mse: 188.1791
Epoch 28/30

1/9 [==>...........................] - ETA: 0s - loss: 0.5470 - mse: 186.1183
6/9 [===================>..........] - ETA: 0s - loss: 0.5487 - mse: 188.9812
9/9 [==============================] - 0s 11ms/step - loss: 0.5500 - mse: 191.6165

9/9 [==============================] - 0s 30ms/step - loss: 0.5500 - mse: 191.6165 - val_loss: 0.6310 - val_mse: 188.1791
Epoch 29/30

1/9 [==>...........................] - ETA: 0s - loss: 0.5252 - mse: 186.6233
6/9 [===================>..........] - ETA: 0s - loss: 0.5297 - mse: 190.8659
9/9 [==============================] - 0s 11ms/step - loss: 0.5309 - mse: 191.6166

9/9 [==============================] - 0s 30ms/step - loss: 0.5309 - mse: 191.6166 - val_loss: 0.5864 - val_mse: 188.1792
Epoch 30/30

1/9 [==>...........................] - ETA: 0s - loss: 0.5005 - mse: 195.5208
5/9 [===============>..............] - ETA: 0s - loss: 0.5078 - mse: 194.6414
9/9 [==============================] - 0s 14ms/step - loss: 0.5050 - mse: 191.6166

9/9 [==============================] - 0s 34ms/step - loss: 0.5050 - mse: 191.6166 - val_loss: 0.6473 - val_mse: 188.1793

Run completed: runs/2023-04-03T22-32-21Z

Training run 5/9 (flags = list(128, 0.01, 1000, 100, "tanh")) 
Using run directory runs/2023-04-03T22-32-31Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 106) %>%
+   layer_dense(units = FLAGS$nodes, activation .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('mse')
+  .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   second_bikes_matrix, second_bikes_train_set$count, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(a .... [TRUNCATED] 
Epoch 1/100

1/9 [==>...........................] - ETA: 3s - loss: 4.8000 - mse: 189.6475
7/9 [======================>.......] - ETA: 0s - loss: 4.2471 - mse: 191.1068
9/9 [==============================] - 0s 8ms/step - loss: 4.1269 - mse: 191.6115

9/9 [==============================] - 1s 88ms/step - loss: 4.1269 - mse: 191.6115 - val_loss: 3.5353 - val_mse: 188.1744
Epoch 2/100

1/9 [==>...........................] - ETA: 0s - loss: 3.5488 - mse: 199.7050
8/9 [=========================>....] - ETA: 0s - loss: 3.3404 - mse: 190.5777
9/9 [==============================] - 0s 8ms/step - loss: 3.3258 - mse: 191.6116

9/9 [==============================] - 0s 28ms/step - loss: 3.3258 - mse: 191.6116 - val_loss: 3.1123 - val_mse: 188.1745
Epoch 3/100

1/9 [==>...........................] - ETA: 0s - loss: 3.1089 - mse: 191.4520
8/9 [=========================>....] - ETA: 0s - loss: 3.0128 - mse: 191.6573
9/9 [==============================] - 0s 8ms/step - loss: 3.0034 - mse: 191.6117

9/9 [==============================] - 0s 27ms/step - loss: 3.0034 - mse: 191.6117 - val_loss: 2.8563 - val_mse: 188.1746
Epoch 4/100

1/9 [==>...........................] - ETA: 0s - loss: 2.8551 - mse: 187.6067
8/9 [=========================>....] - ETA: 0s - loss: 2.7760 - mse: 190.3231
9/9 [==============================] - 0s 8ms/step - loss: 2.7709 - mse: 191.6118

9/9 [==============================] - 0s 27ms/step - loss: 2.7709 - mse: 191.6118 - val_loss: 2.6485 - val_mse: 188.1747
Epoch 5/100

1/9 [==>...........................] - ETA: 0s - loss: 2.6309 - mse: 190.4127
8/9 [=========================>....] - ETA: 0s - loss: 2.5865 - mse: 190.4525
9/9 [==============================] - 0s 8ms/step - loss: 2.5814 - mse: 191.6120

9/9 [==============================] - 0s 26ms/step - loss: 2.5814 - mse: 191.6120 - val_loss: 2.4874 - val_mse: 188.1749
Epoch 6/100

1/9 [==>...........................] - ETA: 0s - loss: 2.4701 - mse: 189.0685
8/9 [=========================>....] - ETA: 0s - loss: 2.4386 - mse: 192.6719
9/9 [==============================] - 0s 8ms/step - loss: 2.4291 - mse: 191.6121

9/9 [==============================] - 0s 27ms/step - loss: 2.4291 - mse: 191.6121 - val_loss: 2.3504 - val_mse: 188.1750
Epoch 7/100

1/9 [==>...........................] - ETA: 0s - loss: 2.3244 - mse: 190.5374
8/9 [=========================>....] - ETA: 0s - loss: 2.3024 - mse: 190.7155
9/9 [==============================] - 0s 8ms/step - loss: 2.3021 - mse: 191.6122

9/9 [==============================] - 0s 27ms/step - loss: 2.3021 - mse: 191.6122 - val_loss: 2.2407 - val_mse: 188.1751
Epoch 8/100

1/9 [==>...........................] - ETA: 0s - loss: 2.2562 - mse: 198.2974
8/9 [=========================>....] - ETA: 0s - loss: 2.1982 - mse: 191.9019
9/9 [==============================] - 0s 8ms/step - loss: 2.1929 - mse: 191.6123

9/9 [==============================] - 0s 27ms/step - loss: 2.1929 - mse: 191.6123 - val_loss: 2.1486 - val_mse: 188.1752
Epoch 9/100

1/9 [==>...........................] - ETA: 0s - loss: 2.1539 - mse: 195.9176
8/9 [=========================>....] - ETA: 0s - loss: 2.1001 - mse: 192.3313
9/9 [==============================] - 0s 8ms/step - loss: 2.0938 - mse: 191.6124

9/9 [==============================] - 0s 27ms/step - loss: 2.0938 - mse: 191.6124 - val_loss: 2.0594 - val_mse: 188.1753
Epoch 10/100

1/9 [==>...........................] - ETA: 0s - loss: 2.0624 - mse: 193.8190
8/9 [=========================>....] - ETA: 0s - loss: 2.0052 - mse: 191.1857
9/9 [==============================] - 0s 7ms/step - loss: 2.0028 - mse: 191.6125

9/9 [==============================] - 0s 27ms/step - loss: 2.0028 - mse: 191.6125 - val_loss: 1.9782 - val_mse: 188.1754
Epoch 11/100

1/9 [==>...........................] - ETA: 0s - loss: 1.9776 - mse: 200.8775
8/9 [=========================>....] - ETA: 0s - loss: 1.9231 - mse: 191.5458
9/9 [==============================] - 0s 7ms/step - loss: 1.9205 - mse: 191.6126

9/9 [==============================] - 0s 29ms/step - loss: 1.9205 - mse: 191.6126 - val_loss: 1.8921 - val_mse: 188.1754
Epoch 12/100

1/9 [==>...........................] - ETA: 0s - loss: 1.8757 - mse: 193.8469
8/9 [=========================>....] - ETA: 0s - loss: 1.8461 - mse: 191.4916
9/9 [==============================] - 0s 8ms/step - loss: 1.8423 - mse: 191.6127

9/9 [==============================] - 0s 27ms/step - loss: 1.8423 - mse: 191.6127 - val_loss: 1.8263 - val_mse: 188.1755
Epoch 13/100

1/9 [==>...........................] - ETA: 0s - loss: 1.7884 - mse: 188.3418
8/9 [=========================>....] - ETA: 0s - loss: 1.7717 - mse: 191.4856
9/9 [==============================] - 0s 8ms/step - loss: 1.7688 - mse: 191.6128

9/9 [==============================] - 0s 26ms/step - loss: 1.7688 - mse: 191.6128 - val_loss: 1.7506 - val_mse: 188.1756
Epoch 14/100

1/9 [==>...........................] - ETA: 0s - loss: 1.7190 - mse: 188.8738
8/9 [=========================>....] - ETA: 0s - loss: 1.7035 - mse: 191.1495
9/9 [==============================] - 0s 8ms/step - loss: 1.7021 - mse: 191.6129

9/9 [==============================] - 0s 27ms/step - loss: 1.7021 - mse: 191.6129 - val_loss: 1.6840 - val_mse: 188.1757
Epoch 15/100

1/9 [==>...........................] - ETA: 0s - loss: 1.6515 - mse: 189.9493
8/9 [=========================>....] - ETA: 0s - loss: 1.6368 - mse: 190.6706
9/9 [==============================] - 0s 8ms/step - loss: 1.6390 - mse: 191.6130

9/9 [==============================] - 0s 27ms/step - loss: 1.6390 - mse: 191.6130 - val_loss: 1.6163 - val_mse: 188.1758
Epoch 16/100

1/9 [==>...........................] - ETA: 0s - loss: 1.6028 - mse: 192.1718
7/9 [======================>.......] - ETA: 0s - loss: 1.5946 - mse: 193.6456
9/9 [==============================] - 0s 8ms/step - loss: 1.5798 - mse: 191.6130

9/9 [==============================] - 0s 28ms/step - loss: 1.5798 - mse: 191.6130 - val_loss: 1.5601 - val_mse: 188.1759
Epoch 17/100

1/9 [==>...........................] - ETA: 0s - loss: 1.5405 - mse: 189.0889
8/9 [=========================>....] - ETA: 0s - loss: 1.5256 - mse: 191.5558
9/9 [==============================] - 0s 8ms/step - loss: 1.5240 - mse: 191.6131

9/9 [==============================] - 0s 27ms/step - loss: 1.5240 - mse: 191.6131 - val_loss: 1.5072 - val_mse: 188.1760
Epoch 18/100

1/9 [==>...........................] - ETA: 0s - loss: 1.4941 - mse: 189.5327
8/9 [=========================>....] - ETA: 0s - loss: 1.4742 - mse: 191.6454
9/9 [==============================] - 0s 8ms/step - loss: 1.4719 - mse: 191.6132

9/9 [==============================] - 0s 26ms/step - loss: 1.4719 - mse: 191.6132 - val_loss: 1.4512 - val_mse: 188.1761
Epoch 19/100

1/9 [==>...........................] - ETA: 0s - loss: 1.4297 - mse: 189.2548
8/9 [=========================>....] - ETA: 0s - loss: 1.4210 - mse: 190.7317
9/9 [==============================] - 0s 8ms/step - loss: 1.4212 - mse: 191.6133

9/9 [==============================] - 0s 27ms/step - loss: 1.4212 - mse: 191.6133 - val_loss: 1.4098 - val_mse: 188.1761
Epoch 20/100

1/9 [==>...........................] - ETA: 0s - loss: 1.3672 - mse: 186.7226
8/9 [=========================>....] - ETA: 0s - loss: 1.3747 - mse: 190.9438
9/9 [==============================] - 0s 8ms/step - loss: 1.3749 - mse: 191.6134

9/9 [==============================] - 0s 26ms/step - loss: 1.3749 - mse: 191.6134 - val_loss: 1.3577 - val_mse: 188.1762
Epoch 21/100

1/9 [==>...........................] - ETA: 0s - loss: 1.3313 - mse: 190.1577
8/9 [=========================>....] - ETA: 0s - loss: 1.3304 - mse: 190.8089
9/9 [==============================] - 0s 8ms/step - loss: 1.3309 - mse: 191.6135

9/9 [==============================] - 0s 27ms/step - loss: 1.3309 - mse: 191.6135 - val_loss: 1.3158 - val_mse: 188.1763
Epoch 22/100

1/9 [==>...........................] - ETA: 0s - loss: 1.2949 - mse: 189.5987
8/9 [=========================>....] - ETA: 0s - loss: 1.2882 - mse: 191.6941
9/9 [==============================] - 0s 8ms/step - loss: 1.2876 - mse: 191.6136

9/9 [==============================] - 0s 26ms/step - loss: 1.2876 - mse: 191.6136 - val_loss: 1.2759 - val_mse: 188.1764
Epoch 23/100

1/9 [==>...........................] - ETA: 0s - loss: 1.2350 - mse: 182.9874
8/9 [=========================>....] - ETA: 0s - loss: 1.2509 - mse: 191.5588
9/9 [==============================] - 0s 8ms/step - loss: 1.2482 - mse: 191.6137

9/9 [==============================] - 0s 27ms/step - loss: 1.2482 - mse: 191.6137 - val_loss: 1.2393 - val_mse: 188.1765
Epoch 24/100

1/9 [==>...........................] - ETA: 0s - loss: 1.1786 - mse: 177.2637
8/9 [=========================>....] - ETA: 0s - loss: 1.2081 - mse: 191.1815
9/9 [==============================] - 0s 8ms/step - loss: 1.2083 - mse: 191.6138

9/9 [==============================] - 0s 27ms/step - loss: 1.2083 - mse: 191.6138 - val_loss: 1.1953 - val_mse: 188.1766
Epoch 25/100

1/9 [==>...........................] - ETA: 0s - loss: 1.1886 - mse: 191.3821
7/9 [======================>.......] - ETA: 0s - loss: 1.1733 - mse: 190.9929
9/9 [==============================] - 0s 8ms/step - loss: 1.1727 - mse: 191.6138

9/9 [==============================] - 0s 27ms/step - loss: 1.1727 - mse: 191.6138 - val_loss: 1.1593 - val_mse: 188.1767
Epoch 26/100

1/9 [==>...........................] - ETA: 0s - loss: 1.1205 - mse: 181.9249
8/9 [=========================>....] - ETA: 0s - loss: 1.1405 - mse: 191.8904
9/9 [==============================] - 0s 8ms/step - loss: 1.1380 - mse: 191.6139

9/9 [==============================] - 0s 27ms/step - loss: 1.1380 - mse: 191.6139 - val_loss: 1.1288 - val_mse: 188.1768
Epoch 27/100

1/9 [==>...........................] - ETA: 0s - loss: 1.1328 - mse: 197.1900
8/9 [=========================>....] - ETA: 0s - loss: 1.1036 - mse: 190.5363
9/9 [==============================] - 0s 8ms/step - loss: 1.1048 - mse: 191.6140

9/9 [==============================] - 0s 27ms/step - loss: 1.1048 - mse: 191.6140 - val_loss: 1.1017 - val_mse: 188.1768
Epoch 28/100

1/9 [==>...........................] - ETA: 0s - loss: 1.1028 - mse: 197.7083
8/9 [=========================>....] - ETA: 0s - loss: 1.0747 - mse: 191.4551
9/9 [==============================] - 0s 8ms/step - loss: 1.0737 - mse: 191.6141

9/9 [==============================] - 0s 27ms/step - loss: 1.0737 - mse: 191.6141 - val_loss: 1.0664 - val_mse: 188.1769
Epoch 29/100

1/9 [==>...........................] - ETA: 0s - loss: 1.0549 - mse: 187.7041
8/9 [=========================>....] - ETA: 0s - loss: 1.0414 - mse: 190.6210
9/9 [==============================] - 0s 8ms/step - loss: 1.0434 - mse: 191.6142

9/9 [==============================] - 0s 27ms/step - loss: 1.0434 - mse: 191.6142 - val_loss: 1.0375 - val_mse: 188.1770
Epoch 30/100

1/9 [==>...........................] - ETA: 0s - loss: 1.0129 - mse: 190.0853
8/9 [=========================>....] - ETA: 0s - loss: 1.0136 - mse: 191.0700
9/9 [==============================] - 0s 8ms/step - loss: 1.0136 - mse: 191.6143

9/9 [==============================] - 0s 27ms/step - loss: 1.0136 - mse: 191.6143 - val_loss: 1.0164 - val_mse: 188.1771
Epoch 31/100

1/9 [==>...........................] - ETA: 0s - loss: 1.0160 - mse: 197.5194
7/9 [======================>.......] - ETA: 0s - loss: 0.9843 - mse: 189.3079
9/9 [==============================] - 0s 8ms/step - loss: 0.9874 - mse: 191.6143

9/9 [==============================] - 0s 27ms/step - loss: 0.9874 - mse: 191.6143 - val_loss: 0.9858 - val_mse: 188.1772
Epoch 32/100

1/9 [==>...........................] - ETA: 0s - loss: 0.9759 - mse: 194.2867
8/9 [=========================>....] - ETA: 0s - loss: 0.9612 - mse: 191.3762
9/9 [==============================] - 0s 8ms/step - loss: 0.9592 - mse: 191.6144

9/9 [==============================] - 0s 26ms/step - loss: 0.9592 - mse: 191.6144 - val_loss: 0.9579 - val_mse: 188.1773
Epoch 33/100

1/9 [==>...........................] - ETA: 0s - loss: 0.9228 - mse: 183.4298
8/9 [=========================>....] - ETA: 0s - loss: 0.9343 - mse: 191.0328
9/9 [==============================] - 0s 8ms/step - loss: 0.9345 - mse: 191.6145

9/9 [==============================] - 0s 27ms/step - loss: 0.9345 - mse: 191.6145 - val_loss: 0.9411 - val_mse: 188.1774
Epoch 34/100

1/9 [==>...........................] - ETA: 0s - loss: 0.9272 - mse: 194.4820
8/9 [=========================>....] - ETA: 0s - loss: 0.9070 - mse: 191.3727
9/9 [==============================] - 0s 8ms/step - loss: 0.9077 - mse: 191.6146

9/9 [==============================] - 0s 26ms/step - loss: 0.9077 - mse: 191.6146 - val_loss: 0.9097 - val_mse: 188.1775
Epoch 35/100

1/9 [==>...........................] - ETA: 0s - loss: 0.9181 - mse: 201.0504
8/9 [=========================>....] - ETA: 0s - loss: 0.8892 - mse: 192.6608
9/9 [==============================] - 0s 8ms/step - loss: 0.8853 - mse: 191.6147

9/9 [==============================] - 0s 27ms/step - loss: 0.8853 - mse: 191.6147 - val_loss: 0.8994 - val_mse: 188.1776
Epoch 36/100

1/9 [==>...........................] - ETA: 0s - loss: 0.8936 - mse: 200.2289
8/9 [=========================>....] - ETA: 0s - loss: 0.8637 - mse: 191.9722
9/9 [==============================] - 0s 8ms/step - loss: 0.8623 - mse: 191.6148

9/9 [==============================] - 0s 27ms/step - loss: 0.8623 - mse: 191.6148 - val_loss: 0.8666 - val_mse: 188.1776
Epoch 37/100

1/9 [==>...........................] - ETA: 0s - loss: 0.8199 - mse: 181.8744
7/9 [======================>.......] - ETA: 0s - loss: 0.8413 - mse: 191.3504
9/9 [==============================] - 0s 8ms/step - loss: 0.8395 - mse: 191.6149

9/9 [==============================] - 0s 28ms/step - loss: 0.8395 - mse: 191.6149 - val_loss: 0.8458 - val_mse: 188.1777
Epoch 38/100

1/9 [==>...........................] - ETA: 0s - loss: 0.8432 - mse: 198.7504
8/9 [=========================>....] - ETA: 0s - loss: 0.8185 - mse: 191.4587
9/9 [==============================] - 0s 8ms/step - loss: 0.8190 - mse: 191.6149

9/9 [==============================] - 0s 29ms/step - loss: 0.8190 - mse: 191.6149 - val_loss: 0.8313 - val_mse: 188.1778
Epoch 39/100

1/9 [==>...........................] - ETA: 0s - loss: 0.8415 - mse: 201.5212
7/9 [======================>.......] - ETA: 0s - loss: 0.7991 - mse: 191.5182
9/9 [==============================] - 0s 8ms/step - loss: 0.7985 - mse: 191.6150

9/9 [==============================] - 0s 29ms/step - loss: 0.7985 - mse: 191.6150 - val_loss: 0.8077 - val_mse: 188.1779
Epoch 40/100

1/9 [==>...........................] - ETA: 0s - loss: 0.7858 - mse: 187.9732
7/9 [======================>.......] - ETA: 0s - loss: 0.7790 - mse: 191.2711
9/9 [==============================] - 0s 10ms/step - loss: 0.7778 - mse: 191.6151

9/9 [==============================] - 0s 29ms/step - loss: 0.7778 - mse: 191.6151 - val_loss: 0.7878 - val_mse: 188.1779
Epoch 41/100

1/9 [==>...........................] - ETA: 0s - loss: 0.7569 - mse: 189.5447
8/9 [=========================>....] - ETA: 0s - loss: 0.7595 - mse: 191.6423
9/9 [==============================] - 0s 8ms/step - loss: 0.7585 - mse: 191.6152

9/9 [==============================] - 0s 27ms/step - loss: 0.7585 - mse: 191.6152 - val_loss: 0.7697 - val_mse: 188.1780
Epoch 42/100

1/9 [==>...........................] - ETA: 0s - loss: 0.7562 - mse: 195.8094
8/9 [=========================>....] - ETA: 0s - loss: 0.7425 - mse: 192.3751
9/9 [==============================] - 0s 8ms/step - loss: 0.7402 - mse: 191.6153

9/9 [==============================] - 0s 29ms/step - loss: 0.7402 - mse: 191.6153 - val_loss: 0.7570 - val_mse: 188.1781
Epoch 43/100

1/9 [==>...........................] - ETA: 0s - loss: 0.7105 - mse: 188.5404
7/9 [======================>.......] - ETA: 0s - loss: 0.7303 - mse: 193.9430
9/9 [==============================] - 0s 9ms/step - loss: 0.7243 - mse: 191.6153

9/9 [==============================] - 0s 28ms/step - loss: 0.7243 - mse: 191.6153 - val_loss: 0.7380 - val_mse: 188.1782
Epoch 44/100

1/9 [==>...........................] - ETA: 0s - loss: 0.7082 - mse: 190.2813
7/9 [======================>.......] - ETA: 0s - loss: 0.7082 - mse: 191.6666
9/9 [==============================] - 0s 8ms/step - loss: 0.7075 - mse: 191.6154

9/9 [==============================] - 0s 27ms/step - loss: 0.7075 - mse: 191.6154 - val_loss: 0.7352 - val_mse: 188.1783
Epoch 45/100

1/9 [==>...........................] - ETA: 0s - loss: 0.7009 - mse: 196.9381
8/9 [=========================>....] - ETA: 0s - loss: 0.6925 - mse: 191.7232
9/9 [==============================] - 0s 8ms/step - loss: 0.6914 - mse: 191.6155

9/9 [==============================] - 0s 28ms/step - loss: 0.6914 - mse: 191.6155 - val_loss: 0.7022 - val_mse: 188.1783
Epoch 46/100

1/9 [==>...........................] - ETA: 0s - loss: 0.6639 - mse: 182.9682
8/9 [=========================>....] - ETA: 0s - loss: 0.6784 - mse: 192.1111
9/9 [==============================] - 0s 8ms/step - loss: 0.6759 - mse: 191.6156

9/9 [==============================] - 0s 26ms/step - loss: 0.6759 - mse: 191.6156 - val_loss: 0.7011 - val_mse: 188.1784
Epoch 47/100

1/9 [==>...........................] - ETA: 0s - loss: 0.6521 - mse: 192.5939
7/9 [======================>.......] - ETA: 0s - loss: 0.6674 - mse: 193.6835
9/9 [==============================] - 0s 8ms/step - loss: 0.6599 - mse: 191.6157

9/9 [==============================] - 0s 29ms/step - loss: 0.6599 - mse: 191.6157 - val_loss: 0.6793 - val_mse: 188.1785
Epoch 48/100

1/9 [==>...........................] - ETA: 0s - loss: 0.6523 - mse: 190.2323
7/9 [======================>.......] - ETA: 0s - loss: 0.6445 - mse: 191.6983
9/9 [==============================] - 0s 9ms/step - loss: 0.6450 - mse: 191.6157

9/9 [==============================] - 0s 30ms/step - loss: 0.6450 - mse: 191.6157 - val_loss: 0.6629 - val_mse: 188.1785
Epoch 49/100

1/9 [==>...........................] - ETA: 0s - loss: 0.5942 - mse: 178.3914
8/9 [=========================>....] - ETA: 0s - loss: 0.6283 - mse: 190.7725
9/9 [==============================] - 0s 8ms/step - loss: 0.6307 - mse: 191.6158

9/9 [==============================] - 0s 26ms/step - loss: 0.6307 - mse: 191.6158 - val_loss: 0.6570 - val_mse: 188.1786
Epoch 50/100

1/9 [==>...........................] - ETA: 0s - loss: 0.6291 - mse: 191.9273
8/9 [=========================>....] - ETA: 0s - loss: 0.6200 - mse: 192.4161
9/9 [==============================] - 0s 8ms/step - loss: 0.6178 - mse: 191.6159

9/9 [==============================] - 0s 27ms/step - loss: 0.6178 - mse: 191.6159 - val_loss: 0.6379 - val_mse: 188.1786
Epoch 51/100

1/9 [==>...........................] - ETA: 0s - loss: 0.6093 - mse: 198.2186
7/9 [======================>.......] - ETA: 0s - loss: 0.6052 - mse: 192.3286
9/9 [==============================] - 0s 8ms/step - loss: 0.6028 - mse: 191.6160

9/9 [==============================] - 0s 28ms/step - loss: 0.6028 - mse: 191.6160 - val_loss: 0.6302 - val_mse: 188.1787
Epoch 52/100

1/9 [==>...........................] - ETA: 0s - loss: 0.6021 - mse: 194.6006
8/9 [=========================>....] - ETA: 0s - loss: 0.5917 - mse: 191.9074
9/9 [==============================] - 0s 8ms/step - loss: 0.5903 - mse: 191.6160

9/9 [==============================] - 0s 27ms/step - loss: 0.5903 - mse: 191.6160 - val_loss: 0.6229 - val_mse: 188.1788
Epoch 53/100

1/9 [==>...........................] - ETA: 0s - loss: 0.5718 - mse: 191.5722
8/9 [=========================>....] - ETA: 0s - loss: 0.5789 - mse: 191.6389
9/9 [==============================] - 0s 8ms/step - loss: 0.5781 - mse: 191.6161

9/9 [==============================] - 0s 27ms/step - loss: 0.5781 - mse: 191.6161 - val_loss: 0.6011 - val_mse: 188.1789
Epoch 54/100

1/9 [==>...........................] - ETA: 0s - loss: 0.5570 - mse: 186.4980
8/9 [=========================>....] - ETA: 0s - loss: 0.5662 - mse: 191.6246
9/9 [==============================] - 0s 8ms/step - loss: 0.5659 - mse: 191.6161

9/9 [==============================] - 0s 27ms/step - loss: 0.5659 - mse: 191.6161 - val_loss: 0.5941 - val_mse: 188.1789
Epoch 55/100

1/9 [==>...........................] - ETA: 0s - loss: 0.5512 - mse: 188.3976
8/9 [=========================>....] - ETA: 0s - loss: 0.5529 - mse: 190.7327
9/9 [==============================] - 0s 8ms/step - loss: 0.5549 - mse: 191.6162

9/9 [==============================] - 0s 27ms/step - loss: 0.5549 - mse: 191.6162 - val_loss: 0.5842 - val_mse: 188.1790
Epoch 56/100

1/9 [==>...........................] - ETA: 0s - loss: 0.5396 - mse: 188.7702
8/9 [=========================>....] - ETA: 0s - loss: 0.5435 - mse: 191.9709
9/9 [==============================] - 0s 8ms/step - loss: 0.5428 - mse: 191.6163

9/9 [==============================] - 0s 28ms/step - loss: 0.5428 - mse: 191.6163 - val_loss: 0.5787 - val_mse: 188.1791
Epoch 57/100

1/9 [==>...........................] - ETA: 0s - loss: 0.5441 - mse: 196.8340
8/9 [=========================>....] - ETA: 0s - loss: 0.5341 - mse: 192.4631
9/9 [==============================] - 0s 8ms/step - loss: 0.5317 - mse: 191.6164

9/9 [==============================] - 0s 26ms/step - loss: 0.5317 - mse: 191.6164 - val_loss: 0.5696 - val_mse: 188.1791
Epoch 58/100

1/9 [==>...........................] - ETA: 0s - loss: 0.5247 - mse: 190.3204
8/9 [=========================>....] - ETA: 0s - loss: 0.5197 - mse: 191.3096
9/9 [==============================] - 0s 8ms/step - loss: 0.5207 - mse: 191.6164

9/9 [==============================] - 0s 26ms/step - loss: 0.5207 - mse: 191.6164 - val_loss: 0.5584 - val_mse: 188.1792
Epoch 59/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4934 - mse: 186.3383
8/9 [=========================>....] - ETA: 0s - loss: 0.5101 - mse: 191.5296
9/9 [==============================] - 0s 8ms/step - loss: 0.5107 - mse: 191.6165

9/9 [==============================] - 0s 27ms/step - loss: 0.5107 - mse: 191.6165 - val_loss: 0.5448 - val_mse: 188.1792
Epoch 60/100

1/9 [==>...........................] - ETA: 0s - loss: 0.5010 - mse: 191.8418
8/9 [=========================>....] - ETA: 0s - loss: 0.5045 - mse: 192.4929
9/9 [==============================] - 0s 8ms/step - loss: 0.5013 - mse: 191.6165

9/9 [==============================] - 0s 27ms/step - loss: 0.5013 - mse: 191.6165 - val_loss: 0.5263 - val_mse: 188.1793
Epoch 61/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4941 - mse: 192.5751
8/9 [=========================>....] - ETA: 0s - loss: 0.4927 - mse: 192.2944
9/9 [==============================] - 0s 8ms/step - loss: 0.4909 - mse: 191.6166

9/9 [==============================] - 0s 26ms/step - loss: 0.4909 - mse: 191.6166 - val_loss: 0.5298 - val_mse: 188.1794
Epoch 62/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4995 - mse: 196.4891
8/9 [=========================>....] - ETA: 0s - loss: 0.4802 - mse: 190.4532
9/9 [==============================] - 0s 8ms/step - loss: 0.4824 - mse: 191.6167

9/9 [==============================] - 0s 26ms/step - loss: 0.4824 - mse: 191.6167 - val_loss: 0.5182 - val_mse: 188.1794
Epoch 63/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4929 - mse: 199.1406
8/9 [=========================>....] - ETA: 0s - loss: 0.4725 - mse: 191.1029
9/9 [==============================] - 0s 8ms/step - loss: 0.4735 - mse: 191.6167

9/9 [==============================] - 0s 26ms/step - loss: 0.4735 - mse: 191.6167 - val_loss: 0.5196 - val_mse: 188.1795
Epoch 64/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4482 - mse: 185.3670
8/9 [=========================>....] - ETA: 0s - loss: 0.4650 - mse: 191.5882
9/9 [==============================] - 0s 8ms/step - loss: 0.4640 - mse: 191.6168

9/9 [==============================] - 0s 27ms/step - loss: 0.4640 - mse: 191.6168 - val_loss: 0.5161 - val_mse: 188.1795
Epoch 65/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4600 - mse: 190.8098
8/9 [=========================>....] - ETA: 0s - loss: 0.4576 - mse: 192.6434
9/9 [==============================] - 0s 8ms/step - loss: 0.4553 - mse: 191.6168

9/9 [==============================] - 0s 26ms/step - loss: 0.4553 - mse: 191.6168 - val_loss: 0.4950 - val_mse: 188.1796
Epoch 66/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4372 - mse: 183.5224
8/9 [=========================>....] - ETA: 0s - loss: 0.4465 - mse: 191.2811
9/9 [==============================] - 0s 8ms/step - loss: 0.4472 - mse: 191.6169

9/9 [==============================] - 0s 27ms/step - loss: 0.4472 - mse: 191.6169 - val_loss: 0.4859 - val_mse: 188.1796
Epoch 67/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4148 - mse: 183.0041
8/9 [=========================>....] - ETA: 0s - loss: 0.4382 - mse: 190.9004
9/9 [==============================] - 0s 8ms/step - loss: 0.4398 - mse: 191.6169

9/9 [==============================] - 0s 26ms/step - loss: 0.4398 - mse: 191.6169 - val_loss: 0.4948 - val_mse: 188.1797
Epoch 68/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4233 - mse: 186.5887
8/9 [=========================>....] - ETA: 0s - loss: 0.4320 - mse: 191.3783
9/9 [==============================] - 0s 8ms/step - loss: 0.4324 - mse: 191.6170

9/9 [==============================] - 0s 26ms/step - loss: 0.4324 - mse: 191.6170 - val_loss: 0.4706 - val_mse: 188.1797
Epoch 69/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4140 - mse: 181.4520
7/9 [======================>.......] - ETA: 0s - loss: 0.4290 - mse: 193.7783
9/9 [==============================] - 0s 8ms/step - loss: 0.4235 - mse: 191.6171

9/9 [==============================] - 0s 26ms/step - loss: 0.4235 - mse: 191.6171 - val_loss: 0.4763 - val_mse: 188.1797
Epoch 70/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4035 - mse: 185.7813
7/9 [======================>.......] - ETA: 0s - loss: 0.4122 - mse: 190.4630
9/9 [==============================] - 0s 8ms/step - loss: 0.4153 - mse: 191.6171

9/9 [==============================] - 0s 29ms/step - loss: 0.4153 - mse: 191.6171 - val_loss: 0.4555 - val_mse: 188.1798
Epoch 71/100

1/9 [==>...........................] - ETA: 0s - loss: 0.4107 - mse: 189.1603
8/9 [=========================>....] - ETA: 0s - loss: 0.4093 - mse: 191.1109
9/9 [==============================] - 0s 8ms/step - loss: 0.4097 - mse: 191.6171

9/9 [==============================] - 0s 26ms/step - loss: 0.4097 - mse: 191.6171 - val_loss: 0.4678 - val_mse: 188.1799
Epoch 72/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3843 - mse: 184.3874
8/9 [=========================>....] - ETA: 0s - loss: 0.4016 - mse: 191.5459
9/9 [==============================] - 0s 8ms/step - loss: 0.4023 - mse: 191.6172

9/9 [==============================] - 0s 27ms/step - loss: 0.4023 - mse: 191.6172 - val_loss: 0.4529 - val_mse: 188.1799
Epoch 73/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3853 - mse: 190.3374
7/9 [======================>.......] - ETA: 0s - loss: 0.3926 - mse: 191.0158
9/9 [==============================] - 0s 8ms/step - loss: 0.3943 - mse: 191.6172

9/9 [==============================] - 0s 29ms/step - loss: 0.3943 - mse: 191.6172 - val_loss: 0.4399 - val_mse: 188.1799
Epoch 74/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3781 - mse: 186.2917
8/9 [=========================>....] - ETA: 0s - loss: 0.3872 - mse: 191.4647
9/9 [==============================] - 0s 8ms/step - loss: 0.3879 - mse: 191.6173

9/9 [==============================] - 0s 28ms/step - loss: 0.3879 - mse: 191.6173 - val_loss: 0.4525 - val_mse: 188.1800
Epoch 75/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3713 - mse: 190.5184
8/9 [=========================>....] - ETA: 0s - loss: 0.3810 - mse: 191.2603
9/9 [==============================] - 0s 8ms/step - loss: 0.3814 - mse: 191.6173

9/9 [==============================] - 0s 26ms/step - loss: 0.3814 - mse: 191.6173 - val_loss: 0.4279 - val_mse: 188.1800
Epoch 76/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3906 - mse: 195.2351
8/9 [=========================>....] - ETA: 0s - loss: 0.3775 - mse: 192.1013
9/9 [==============================] - 0s 8ms/step - loss: 0.3759 - mse: 191.6174

9/9 [==============================] - 0s 28ms/step - loss: 0.3759 - mse: 191.6174 - val_loss: 0.4355 - val_mse: 188.1801
Epoch 77/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3774 - mse: 194.1141
8/9 [=========================>....] - ETA: 0s - loss: 0.3685 - mse: 191.5211
9/9 [==============================] - 0s 8ms/step - loss: 0.3687 - mse: 191.6174

9/9 [==============================] - 0s 27ms/step - loss: 0.3687 - mse: 191.6174 - val_loss: 0.4241 - val_mse: 188.1801
Epoch 78/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3751 - mse: 196.5395
8/9 [=========================>....] - ETA: 0s - loss: 0.3616 - mse: 191.4564
9/9 [==============================] - 0s 8ms/step - loss: 0.3626 - mse: 191.6175

9/9 [==============================] - 0s 27ms/step - loss: 0.3626 - mse: 191.6175 - val_loss: 0.4156 - val_mse: 188.1802
Epoch 79/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3552 - mse: 195.0169
7/9 [======================>.......] - ETA: 0s - loss: 0.3558 - mse: 191.4055
9/9 [==============================] - 0s 8ms/step - loss: 0.3580 - mse: 191.6175

9/9 [==============================] - 0s 27ms/step - loss: 0.3580 - mse: 191.6175 - val_loss: 0.4359 - val_mse: 188.1802
Epoch 80/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3523 - mse: 185.0332
8/9 [=========================>....] - ETA: 0s - loss: 0.3539 - mse: 192.3351
9/9 [==============================] - 0s 8ms/step - loss: 0.3522 - mse: 191.6176

9/9 [==============================] - 0s 27ms/step - loss: 0.3522 - mse: 191.6176 - val_loss: 0.4176 - val_mse: 188.1802
Epoch 81/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3667 - mse: 198.1134
8/9 [=========================>....] - ETA: 0s - loss: 0.3486 - mse: 191.4650
9/9 [==============================] - 0s 8ms/step - loss: 0.3484 - mse: 191.6176

9/9 [==============================] - 0s 27ms/step - loss: 0.3484 - mse: 191.6176 - val_loss: 0.3972 - val_mse: 188.1803
Epoch 82/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3376 - mse: 189.6256
8/9 [=========================>....] - ETA: 0s - loss: 0.3427 - mse: 192.4151
9/9 [==============================] - 0s 8ms/step - loss: 0.3410 - mse: 191.6176

9/9 [==============================] - 0s 27ms/step - loss: 0.3410 - mse: 191.6176 - val_loss: 0.4030 - val_mse: 188.1803
Epoch 83/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3335 - mse: 189.0742
8/9 [=========================>....] - ETA: 0s - loss: 0.3340 - mse: 191.1989
9/9 [==============================] - 0s 8ms/step - loss: 0.3355 - mse: 191.6177

9/9 [==============================] - 0s 27ms/step - loss: 0.3355 - mse: 191.6177 - val_loss: 0.3832 - val_mse: 188.1804
Epoch 84/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3433 - mse: 195.1601
7/9 [======================>.......] - ETA: 0s - loss: 0.3319 - mse: 191.2854
9/9 [==============================] - 0s 9ms/step - loss: 0.3323 - mse: 191.6177

9/9 [==============================] - 0s 28ms/step - loss: 0.3323 - mse: 191.6177 - val_loss: 0.3944 - val_mse: 188.1804
Epoch 85/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3114 - mse: 190.0864
7/9 [======================>.......] - ETA: 0s - loss: 0.3256 - mse: 191.1473
9/9 [==============================] - 0s 9ms/step - loss: 0.3282 - mse: 191.6177

9/9 [==============================] - 0s 28ms/step - loss: 0.3282 - mse: 191.6177 - val_loss: 0.3892 - val_mse: 188.1804
Epoch 86/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3237 - mse: 193.5727
8/9 [=========================>....] - ETA: 0s - loss: 0.3220 - mse: 191.5275
9/9 [==============================] - 0s 8ms/step - loss: 0.3211 - mse: 191.6178

9/9 [==============================] - 0s 27ms/step - loss: 0.3211 - mse: 191.6178 - val_loss: 0.3724 - val_mse: 188.1805
Epoch 87/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3204 - mse: 186.8435
8/9 [=========================>....] - ETA: 0s - loss: 0.3163 - mse: 191.6075
9/9 [==============================] - 0s 8ms/step - loss: 0.3156 - mse: 191.6178

9/9 [==============================] - 0s 29ms/step - loss: 0.3156 - mse: 191.6178 - val_loss: 0.3819 - val_mse: 188.1805
Epoch 88/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3280 - mse: 199.3335
7/9 [======================>.......] - ETA: 0s - loss: 0.3160 - mse: 194.1233
9/9 [==============================] - 0s 8ms/step - loss: 0.3115 - mse: 191.6179

9/9 [==============================] - 0s 28ms/step - loss: 0.3115 - mse: 191.6179 - val_loss: 0.3852 - val_mse: 188.1805
Epoch 89/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2938 - mse: 184.1050
7/9 [======================>.......] - ETA: 0s - loss: 0.3031 - mse: 189.4900
9/9 [==============================] - 0s 8ms/step - loss: 0.3066 - mse: 191.6179

9/9 [==============================] - 0s 26ms/step - loss: 0.3066 - mse: 191.6179 - val_loss: 0.3749 - val_mse: 188.1806
Epoch 90/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2897 - mse: 186.0168
8/9 [=========================>....] - ETA: 0s - loss: 0.3026 - mse: 191.9877
9/9 [==============================] - 0s 8ms/step - loss: 0.3025 - mse: 191.6179

9/9 [==============================] - 0s 27ms/step - loss: 0.3025 - mse: 191.6179 - val_loss: 0.3580 - val_mse: 188.1806
Epoch 91/100

1/9 [==>...........................] - ETA: 0s - loss: 0.3203 - mse: 197.8116
7/9 [======================>.......] - ETA: 0s - loss: 0.3018 - mse: 192.2471
9/9 [==============================] - 0s 8ms/step - loss: 0.2992 - mse: 191.6180

9/9 [==============================] - 0s 27ms/step - loss: 0.2992 - mse: 191.6180 - val_loss: 0.3953 - val_mse: 188.1806
Epoch 92/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2775 - mse: 181.9829
8/9 [=========================>....] - ETA: 0s - loss: 0.2971 - mse: 191.6217
9/9 [==============================] - 0s 8ms/step - loss: 0.2973 - mse: 191.6180

9/9 [==============================] - 0s 26ms/step - loss: 0.2973 - mse: 191.6180 - val_loss: 0.3435 - val_mse: 188.1806
Epoch 93/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2661 - mse: 181.9129
8/9 [=========================>....] - ETA: 0s - loss: 0.2896 - mse: 190.9312
9/9 [==============================] - 0s 8ms/step - loss: 0.2914 - mse: 191.6180

9/9 [==============================] - 0s 26ms/step - loss: 0.2914 - mse: 191.6180 - val_loss: 0.3898 - val_mse: 188.1807
Epoch 94/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2922 - mse: 183.4702
8/9 [=========================>....] - ETA: 0s - loss: 0.2872 - mse: 191.0571
9/9 [==============================] - 0s 8ms/step - loss: 0.2877 - mse: 191.6181

9/9 [==============================] - 0s 26ms/step - loss: 0.2877 - mse: 191.6181 - val_loss: 0.3480 - val_mse: 188.1807
Epoch 95/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2947 - mse: 196.6101
8/9 [=========================>....] - ETA: 0s - loss: 0.2811 - mse: 190.6968
9/9 [==============================] - 0s 8ms/step - loss: 0.2822 - mse: 191.6181

9/9 [==============================] - 0s 27ms/step - loss: 0.2822 - mse: 191.6181 - val_loss: 0.3567 - val_mse: 188.1808
Epoch 96/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2576 - mse: 179.8336
8/9 [=========================>....] - ETA: 0s - loss: 0.2753 - mse: 190.0966
9/9 [==============================] - 0s 8ms/step - loss: 0.2783 - mse: 191.6181

9/9 [==============================] - 0s 27ms/step - loss: 0.2783 - mse: 191.6181 - val_loss: 0.3440 - val_mse: 188.1808
Epoch 97/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2790 - mse: 195.5982
8/9 [=========================>....] - ETA: 0s - loss: 0.2744 - mse: 191.6851
9/9 [==============================] - 0s 8ms/step - loss: 0.2749 - mse: 191.6181

9/9 [==============================] - 0s 27ms/step - loss: 0.2749 - mse: 191.6181 - val_loss: 0.3374 - val_mse: 188.1808
Epoch 98/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2817 - mse: 197.2621
8/9 [=========================>....] - ETA: 0s - loss: 0.2716 - mse: 192.2540
9/9 [==============================] - 0s 8ms/step - loss: 0.2705 - mse: 191.6182

9/9 [==============================] - 0s 26ms/step - loss: 0.2705 - mse: 191.6182 - val_loss: 0.3440 - val_mse: 188.1808
Epoch 99/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2665 - mse: 195.5985
8/9 [=========================>....] - ETA: 0s - loss: 0.2695 - mse: 192.1508
9/9 [==============================] - 0s 8ms/step - loss: 0.2673 - mse: 191.6182

9/9 [==============================] - 0s 26ms/step - loss: 0.2673 - mse: 191.6182 - val_loss: 0.3283 - val_mse: 188.1809
Epoch 100/100

1/9 [==>...........................] - ETA: 0s - loss: 0.2554 - mse: 190.1570
8/9 [=========================>....] - ETA: 0s - loss: 0.2669 - mse: 193.3505
9/9 [==============================] - 0s 8ms/step - loss: 0.2639 - mse: 191.6182

9/9 [==============================] - 0s 26ms/step - loss: 0.2639 - mse: 191.6182 - val_loss: 0.3385 - val_mse: 188.1809

Run completed: runs/2023-04-03T22-32-31Z

Training run 6/9 (flags = list(392, 0.01, 200, 100, "relu")) 
Using run directory runs/2023-04-03T22-32-55Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 106) %>%
+   layer_dense(units = FLAGS$nodes, activation .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('mse')
+  .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   second_bikes_matrix, second_bikes_train_set$count, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(a .... [TRUNCATED] 
Epoch 1/100

 1/45 [..............................] - ETA: 14s - loss: 4.9198 - mse: 200.2556
 7/45 [===>..........................] - ETA: 0s - loss: 4.0612 - mse: 192.3781 
13/45 [=======>......................] - ETA: 0s - loss: 3.6981 - mse: 189.9896
19/45 [===========>..................] - ETA: 0s - loss: 3.4669 - mse: 192.6887
25/45 [===============>..............] - ETA: 0s - loss: 3.2894 - mse: 191.5632
31/45 [===================>..........] - ETA: 0s - loss: 3.1355 - mse: 191.2267
37/45 [=======================>......] - ETA: 0s - loss: 3.0116 - mse: 191.2683
43/45 [===========================>..] - ETA: 0s - loss: 2.9065 - mse: 191.6398
45/45 [==============================] - 1s 9ms/step - loss: 2.8885 - mse: 191.6121

45/45 [==============================] - 1s 24ms/step - loss: 2.8885 - mse: 191.6121 - val_loss: 2.1428 - val_mse: 188.1755
Epoch 2/100

 1/45 [..............................] - ETA: 0s - loss: 2.1297 - mse: 194.3645
 7/45 [===>..........................] - ETA: 0s - loss: 2.0373 - mse: 191.1121
13/45 [=======>......................] - ETA: 0s - loss: 2.0193 - mse: 190.7284
19/45 [===========>..................] - ETA: 0s - loss: 1.9814 - mse: 191.7350
25/45 [===============>..............] - ETA: 0s - loss: 1.9446 - mse: 192.5507
31/45 [===================>..........] - ETA: 0s - loss: 1.9241 - mse: 194.1882
37/45 [=======================>......] - ETA: 0s - loss: 1.8855 - mse: 192.1166
43/45 [===========================>..] - ETA: 0s - loss: 1.8538 - mse: 191.8177
45/45 [==============================] - 0s 9ms/step - loss: 1.8485 - mse: 191.6130

45/45 [==============================] - 1s 13ms/step - loss: 1.8485 - mse: 191.6130 - val_loss: 1.6460 - val_mse: 188.1762
Epoch 3/100

 1/45 [..............................] - ETA: 0s - loss: 1.5443 - mse: 185.1544
 7/45 [===>..........................] - ETA: 0s - loss: 1.6096 - mse: 193.1268
13/45 [=======>......................] - ETA: 0s - loss: 1.5848 - mse: 192.5011
19/45 [===========>..................] - ETA: 0s - loss: 1.5531 - mse: 191.2322
25/45 [===============>..............] - ETA: 0s - loss: 1.5337 - mse: 190.4412
31/45 [===================>..........] - ETA: 0s - loss: 1.5139 - mse: 191.1172
37/45 [=======================>......] - ETA: 0s - loss: 1.5032 - mse: 190.7304
43/45 [===========================>..] - ETA: 0s - loss: 1.4919 - mse: 191.9504
45/45 [==============================] - 0s 9ms/step - loss: 1.4884 - mse: 191.6138

45/45 [==============================] - 1s 12ms/step - loss: 1.4884 - mse: 191.6138 - val_loss: 1.3967 - val_mse: 188.1768
Epoch 4/100

 1/45 [..............................] - ETA: 0s - loss: 1.3221 - mse: 210.3982
 7/45 [===>..........................] - ETA: 0s - loss: 1.3064 - mse: 188.8098
13/45 [=======>......................] - ETA: 0s - loss: 1.2851 - mse: 187.3837
19/45 [===========>..................] - ETA: 0s - loss: 1.2539 - mse: 187.5672
25/45 [===============>..............] - ETA: 0s - loss: 1.2362 - mse: 186.5659
31/45 [===================>..........] - ETA: 0s - loss: 1.2267 - mse: 188.0141
37/45 [=======================>......] - ETA: 0s - loss: 1.2166 - mse: 190.3275
43/45 [===========================>..] - ETA: 0s - loss: 1.2047 - mse: 191.6573
45/45 [==============================] - 0s 9ms/step - loss: 1.2017 - mse: 191.6142

45/45 [==============================] - 1s 13ms/step - loss: 1.2017 - mse: 191.6142 - val_loss: 1.1319 - val_mse: 188.1773
Epoch 5/100

 1/45 [..............................] - ETA: 0s - loss: 1.1081 - mse: 210.1568
 7/45 [===>..........................] - ETA: 0s - loss: 1.0969 - mse: 192.4108
13/45 [=======>......................] - ETA: 0s - loss: 1.0719 - mse: 188.0226
18/45 [===========>..................] - ETA: 0s - loss: 1.0558 - mse: 187.8588
24/45 [===============>..............] - ETA: 0s - loss: 1.0491 - mse: 190.4009
30/45 [===================>..........] - ETA: 0s - loss: 1.0380 - mse: 191.6511
36/45 [=======================>......] - ETA: 0s - loss: 1.0261 - mse: 192.3524
42/45 [===========================>..] - ETA: 0s - loss: 1.0202 - mse: 191.6111
45/45 [==============================] - 0s 9ms/step - loss: 1.0153 - mse: 191.6147

45/45 [==============================] - 1s 13ms/step - loss: 1.0153 - mse: 191.6147 - val_loss: 1.0196 - val_mse: 188.1780
Epoch 6/100

 1/45 [..............................] - ETA: 0s - loss: 0.9003 - mse: 177.1181
 7/45 [===>..........................] - ETA: 0s - loss: 0.9671 - mse: 190.4885
13/45 [=======>......................] - ETA: 0s - loss: 0.9510 - mse: 190.1913
19/45 [===========>..................] - ETA: 0s - loss: 0.9409 - mse: 190.8378
25/45 [===============>..............] - ETA: 0s - loss: 0.9414 - mse: 192.5053
31/45 [===================>..........] - ETA: 0s - loss: 0.9322 - mse: 191.8996
37/45 [=======================>......] - ETA: 0s - loss: 0.9251 - mse: 190.8981
43/45 [===========================>..] - ETA: 0s - loss: 0.9124 - mse: 191.2515
45/45 [==============================] - 0s 9ms/step - loss: 0.9110 - mse: 191.6153

45/45 [==============================] - 1s 13ms/step - loss: 0.9110 - mse: 191.6153 - val_loss: 0.9218 - val_mse: 188.1781
Epoch 7/100

 1/45 [..............................] - ETA: 0s - loss: 0.7880 - mse: 196.9327
 7/45 [===>..........................] - ETA: 0s - loss: 0.8409 - mse: 198.3103
13/45 [=======>......................] - ETA: 0s - loss: 0.8521 - mse: 197.8237
19/45 [===========>..................] - ETA: 0s - loss: 0.8292 - mse: 194.4749
25/45 [===============>..............] - ETA: 0s - loss: 0.8189 - mse: 193.2579
31/45 [===================>..........] - ETA: 0s - loss: 0.8048 - mse: 192.3487
37/45 [=======================>......] - ETA: 0s - loss: 0.7986 - mse: 192.2598
43/45 [===========================>..] - ETA: 0s - loss: 0.7883 - mse: 191.7206
45/45 [==============================] - 0s 9ms/step - loss: 0.7859 - mse: 191.6156

45/45 [==============================] - 1s 13ms/step - loss: 0.7859 - mse: 191.6156 - val_loss: 0.9033 - val_mse: 188.1787
Epoch 8/100

 1/45 [..............................] - ETA: 0s - loss: 0.7870 - mse: 189.0618
 7/45 [===>..........................] - ETA: 0s - loss: 0.7607 - mse: 191.4473
13/45 [=======>......................] - ETA: 0s - loss: 0.7425 - mse: 191.6286
19/45 [===========>..................] - ETA: 0s - loss: 0.7423 - mse: 192.7599
25/45 [===============>..............] - ETA: 0s - loss: 0.7308 - mse: 192.0046
31/45 [===================>..........] - ETA: 0s - loss: 0.7270 - mse: 191.6031
37/45 [=======================>......] - ETA: 0s - loss: 0.7219 - mse: 191.4508
43/45 [===========================>..] - ETA: 0s - loss: 0.7200 - mse: 191.4289
45/45 [==============================] - 0s 9ms/step - loss: 0.7185 - mse: 191.6160

45/45 [==============================] - 1s 13ms/step - loss: 0.7185 - mse: 191.6160 - val_loss: 0.7775 - val_mse: 188.1788
Epoch 9/100

 1/45 [..............................] - ETA: 0s - loss: 0.6203 - mse: 172.2785
 7/45 [===>..........................] - ETA: 0s - loss: 0.6612 - mse: 191.1210
13/45 [=======>......................] - ETA: 0s - loss: 0.6671 - mse: 192.0111
18/45 [===========>..................] - ETA: 0s - loss: 0.6612 - mse: 191.6646
24/45 [===============>..............] - ETA: 0s - loss: 0.6581 - mse: 192.5335
30/45 [===================>..........] - ETA: 0s - loss: 0.6523 - mse: 192.4662
36/45 [=======================>......] - ETA: 0s - loss: 0.6444 - mse: 191.1126
42/45 [===========================>..] - ETA: 0s - loss: 0.6363 - mse: 191.4586
45/45 [==============================] - 0s 9ms/step - loss: 0.6344 - mse: 191.6163

45/45 [==============================] - 1s 13ms/step - loss: 0.6344 - mse: 191.6163 - val_loss: 0.7467 - val_mse: 188.1791
Epoch 10/100

 1/45 [..............................] - ETA: 0s - loss: 0.7049 - mse: 220.7894
 7/45 [===>..........................] - ETA: 0s - loss: 0.6416 - mse: 196.9710
13/45 [=======>......................] - ETA: 0s - loss: 0.6496 - mse: 195.7920
18/45 [===========>..................] - ETA: 0s - loss: 0.6292 - mse: 195.1791
23/45 [==============>...............] - ETA: 0s - loss: 0.6188 - mse: 191.7488
28/45 [=================>............] - ETA: 0s - loss: 0.6138 - mse: 191.9265
33/45 [=====================>........] - ETA: 0s - loss: 0.6128 - mse: 192.4598
39/45 [=========================>....] - ETA: 0s - loss: 0.6096 - mse: 192.2817
45/45 [==============================] - 0s 10ms/step - loss: 0.6024 - mse: 191.6166

45/45 [==============================] - 1s 13ms/step - loss: 0.6024 - mse: 191.6166 - val_loss: 0.7026 - val_mse: 188.1795
Epoch 11/100

 1/45 [..............................] - ETA: 0s - loss: 0.5950 - mse: 187.7778
 7/45 [===>..........................] - ETA: 0s - loss: 0.5965 - mse: 191.1158
13/45 [=======>......................] - ETA: 0s - loss: 0.5755 - mse: 192.1160
19/45 [===========>..................] - ETA: 0s - loss: 0.5649 - mse: 192.5055
25/45 [===============>..............] - ETA: 0s - loss: 0.5545 - mse: 192.1958
31/45 [===================>..........] - ETA: 0s - loss: 0.5474 - mse: 191.9879
37/45 [=======================>......] - ETA: 0s - loss: 0.5393 - mse: 193.0013
43/45 [===========================>..] - ETA: 0s - loss: 0.5325 - mse: 192.1298
45/45 [==============================] - 0s 9ms/step - loss: 0.5309 - mse: 191.6168

45/45 [==============================] - 1s 13ms/step - loss: 0.5309 - mse: 191.6168 - val_loss: 0.5988 - val_mse: 188.1796
Epoch 12/100

 1/45 [..............................] - ETA: 0s - loss: 0.4904 - mse: 193.1384
 7/45 [===>..........................] - ETA: 0s - loss: 0.5097 - mse: 195.0190
13/45 [=======>......................] - ETA: 0s - loss: 0.4991 - mse: 194.3552
19/45 [===========>..................] - ETA: 0s - loss: 0.4986 - mse: 193.8887
25/45 [===============>..............] - ETA: 0s - loss: 0.4990 - mse: 193.7012
31/45 [===================>..........] - ETA: 0s - loss: 0.4916 - mse: 192.3369
37/45 [=======================>......] - ETA: 0s - loss: 0.4891 - mse: 192.2282
43/45 [===========================>..] - ETA: 0s - loss: 0.4897 - mse: 192.2242
45/45 [==============================] - 0s 9ms/step - loss: 0.4888 - mse: 191.6171

45/45 [==============================] - 1s 13ms/step - loss: 0.4888 - mse: 191.6171 - val_loss: 0.6243 - val_mse: 188.1799
Epoch 13/100

 1/45 [..............................] - ETA: 0s - loss: 0.5190 - mse: 195.0418
 7/45 [===>..........................] - ETA: 0s - loss: 0.5001 - mse: 200.2275
13/45 [=======>......................] - ETA: 0s - loss: 0.4934 - mse: 196.8316
19/45 [===========>..................] - ETA: 0s - loss: 0.4953 - mse: 197.5934
25/45 [===============>..............] - ETA: 0s - loss: 0.4853 - mse: 193.8618
31/45 [===================>..........] - ETA: 0s - loss: 0.4816 - mse: 192.7627
37/45 [=======================>......] - ETA: 0s - loss: 0.4812 - mse: 192.5851
43/45 [===========================>..] - ETA: 0s - loss: 0.4768 - mse: 191.9392
45/45 [==============================] - 0s 9ms/step - loss: 0.4750 - mse: 191.6173

45/45 [==============================] - 1s 12ms/step - loss: 0.4750 - mse: 191.6173 - val_loss: 0.6389 - val_mse: 188.1802
Epoch 14/100

 1/45 [..............................] - ETA: 0s - loss: 0.5929 - mse: 199.8033
 7/45 [===>..........................] - ETA: 0s - loss: 0.5111 - mse: 198.7471
13/45 [=======>......................] - ETA: 0s - loss: 0.4702 - mse: 194.9896
19/45 [===========>..................] - ETA: 0s - loss: 0.4566 - mse: 194.7051
25/45 [===============>..............] - ETA: 0s - loss: 0.4486 - mse: 193.7138
31/45 [===================>..........] - ETA: 0s - loss: 0.4460 - mse: 194.6219
37/45 [=======================>......] - ETA: 0s - loss: 0.4497 - mse: 193.0731
43/45 [===========================>..] - ETA: 0s - loss: 0.4470 - mse: 191.4751
45/45 [==============================] - 0s 9ms/step - loss: 0.4468 - mse: 191.6175

45/45 [==============================] - 1s 13ms/step - loss: 0.4468 - mse: 191.6175 - val_loss: 0.5115 - val_mse: 188.1801
Epoch 15/100

 1/45 [..............................] - ETA: 0s - loss: 0.4969 - mse: 195.2011
 7/45 [===>..........................] - ETA: 0s - loss: 0.4574 - mse: 197.6570
13/45 [=======>......................] - ETA: 0s - loss: 0.4445 - mse: 193.9361
19/45 [===========>..................] - ETA: 0s - loss: 0.4293 - mse: 190.7934
25/45 [===============>..............] - ETA: 0s - loss: 0.4254 - mse: 191.0503
31/45 [===================>..........] - ETA: 0s - loss: 0.4297 - mse: 192.3755
37/45 [=======================>......] - ETA: 0s - loss: 0.4275 - mse: 192.6149
43/45 [===========================>..] - ETA: 0s - loss: 0.4267 - mse: 191.7821
45/45 [==============================] - 0s 9ms/step - loss: 0.4262 - mse: 191.6176

45/45 [==============================] - 1s 13ms/step - loss: 0.4262 - mse: 191.6176 - val_loss: 0.5635 - val_mse: 188.1805
Epoch 16/100

 1/45 [..............................] - ETA: 0s - loss: 0.4575 - mse: 181.8188
 7/45 [===>..........................] - ETA: 0s - loss: 0.4898 - mse: 186.1418
13/45 [=======>......................] - ETA: 0s - loss: 0.4812 - mse: 189.5960
19/45 [===========>..................] - ETA: 0s - loss: 0.4743 - mse: 191.9617
25/45 [===============>..............] - ETA: 0s - loss: 0.4678 - mse: 191.2567
31/45 [===================>..........] - ETA: 0s - loss: 0.4562 - mse: 190.3760
37/45 [=======================>......] - ETA: 0s - loss: 0.4438 - mse: 189.6940
43/45 [===========================>..] - ETA: 0s - loss: 0.4328 - mse: 191.2393
45/45 [==============================] - 0s 9ms/step - loss: 0.4324 - mse: 191.6178

45/45 [==============================] - 1s 13ms/step - loss: 0.4324 - mse: 191.6178 - val_loss: 0.4991 - val_mse: 188.1805
Epoch 17/100

 1/45 [..............................] - ETA: 0s - loss: 0.3571 - mse: 204.2039
 7/45 [===>..........................] - ETA: 0s - loss: 0.3813 - mse: 187.7367
13/45 [=======>......................] - ETA: 0s - loss: 0.3891 - mse: 189.9257
19/45 [===========>..................] - ETA: 0s - loss: 0.3788 - mse: 190.7006
25/45 [===============>..............] - ETA: 0s - loss: 0.3730 - mse: 191.1823
31/45 [===================>..........] - ETA: 0s - loss: 0.3759 - mse: 190.8165
37/45 [=======================>......] - ETA: 0s - loss: 0.3775 - mse: 191.8846
42/45 [===========================>..] - ETA: 0s - loss: 0.3760 - mse: 191.3228
45/45 [==============================] - 0s 9ms/step - loss: 0.3753 - mse: 191.6179

45/45 [==============================] - 1s 13ms/step - loss: 0.3753 - mse: 191.6179 - val_loss: 0.4827 - val_mse: 188.1805
Epoch 18/100

 1/45 [..............................] - ETA: 0s - loss: 0.3875 - mse: 190.4911
 7/45 [===>..........................] - ETA: 0s - loss: 0.3864 - mse: 188.6511
13/45 [=======>......................] - ETA: 0s - loss: 0.3597 - mse: 187.7919
19/45 [===========>..................] - ETA: 0s - loss: 0.3502 - mse: 189.3976
25/45 [===============>..............] - ETA: 0s - loss: 0.3445 - mse: 190.9448
31/45 [===================>..........] - ETA: 0s - loss: 0.3419 - mse: 191.7712
37/45 [=======================>......] - ETA: 0s - loss: 0.3387 - mse: 190.9238
43/45 [===========================>..] - ETA: 0s - loss: 0.3391 - mse: 191.4941
45/45 [==============================] - 0s 9ms/step - loss: 0.3383 - mse: 191.6180

45/45 [==============================] - 1s 13ms/step - loss: 0.3383 - mse: 191.6180 - val_loss: 0.4986 - val_mse: 188.1807
Epoch 19/100

 1/45 [..............................] - ETA: 0s - loss: 0.3122 - mse: 166.8293
 7/45 [===>..........................] - ETA: 0s - loss: 0.3695 - mse: 192.7044
13/45 [=======>......................] - ETA: 0s - loss: 0.3551 - mse: 190.1388
19/45 [===========>..................] - ETA: 0s - loss: 0.3589 - mse: 190.0998
25/45 [===============>..............] - ETA: 0s - loss: 0.3535 - mse: 192.3581
31/45 [===================>..........] - ETA: 0s - loss: 0.3461 - mse: 191.3886
37/45 [=======================>......] - ETA: 0s - loss: 0.3411 - mse: 191.6399
43/45 [===========================>..] - ETA: 0s - loss: 0.3407 - mse: 191.4117
45/45 [==============================] - 0s 9ms/step - loss: 0.3410 - mse: 191.6182

45/45 [==============================] - 1s 13ms/step - loss: 0.3410 - mse: 191.6182 - val_loss: 0.4988 - val_mse: 188.1807
Epoch 20/100

 1/45 [..............................] - ETA: 0s - loss: 0.2530 - mse: 172.8375
 7/45 [===>..........................] - ETA: 0s - loss: 0.3511 - mse: 191.4192
13/45 [=======>......................] - ETA: 0s - loss: 0.3544 - mse: 194.1206
19/45 [===========>..................] - ETA: 0s - loss: 0.3565 - mse: 195.1683
25/45 [===============>..............] - ETA: 0s - loss: 0.3587 - mse: 194.7312
31/45 [===================>..........] - ETA: 0s - loss: 0.3634 - mse: 192.2572
37/45 [=======================>......] - ETA: 0s - loss: 0.3594 - mse: 192.5691
43/45 [===========================>..] - ETA: 0s - loss: 0.3580 - mse: 191.5370
45/45 [==============================] - 0s 9ms/step - loss: 0.3566 - mse: 191.6182

45/45 [==============================] - 1s 13ms/step - loss: 0.3566 - mse: 191.6182 - val_loss: 0.4896 - val_mse: 188.1810
Epoch 21/100

 1/45 [..............................] - ETA: 0s - loss: 0.3459 - mse: 215.6294
 7/45 [===>..........................] - ETA: 0s - loss: 0.3760 - mse: 191.4416
13/45 [=======>......................] - ETA: 0s - loss: 0.3437 - mse: 192.1786
19/45 [===========>..................] - ETA: 0s - loss: 0.3245 - mse: 191.9533
25/45 [===============>..............] - ETA: 0s - loss: 0.3164 - mse: 192.3609
31/45 [===================>..........] - ETA: 0s - loss: 0.3115 - mse: 191.9374
37/45 [=======================>......] - ETA: 0s - loss: 0.3076 - mse: 192.2065
43/45 [===========================>..] - ETA: 0s - loss: 0.3061 - mse: 191.7799
45/45 [==============================] - 0s 9ms/step - loss: 0.3051 - mse: 191.6184

45/45 [==============================] - 1s 13ms/step - loss: 0.3051 - mse: 191.6184 - val_loss: 0.4823 - val_mse: 188.1811
Epoch 22/100

 1/45 [..............................] - ETA: 0s - loss: 0.2946 - mse: 176.9173
 7/45 [===>..........................] - ETA: 0s - loss: 0.2912 - mse: 195.7040
13/45 [=======>......................] - ETA: 0s - loss: 0.2820 - mse: 197.7884
19/45 [===========>..................] - ETA: 0s - loss: 0.2762 - mse: 195.1087
25/45 [===============>..............] - ETA: 0s - loss: 0.2755 - mse: 193.8413
31/45 [===================>..........] - ETA: 0s - loss: 0.2761 - mse: 192.0482
37/45 [=======================>......] - ETA: 0s - loss: 0.2736 - mse: 191.4449
43/45 [===========================>..] - ETA: 0s - loss: 0.2735 - mse: 192.0690
45/45 [==============================] - 0s 9ms/step - loss: 0.2729 - mse: 191.6185

45/45 [==============================] - 1s 13ms/step - loss: 0.2729 - mse: 191.6185 - val_loss: 0.4695 - val_mse: 188.1810
Epoch 23/100

 1/45 [..............................] - ETA: 0s - loss: 0.2740 - mse: 180.3644
 7/45 [===>..........................] - ETA: 0s - loss: 0.3050 - mse: 187.8158
13/45 [=======>......................] - ETA: 0s - loss: 0.2961 - mse: 187.7005
19/45 [===========>..................] - ETA: 0s - loss: 0.2894 - mse: 189.2292
25/45 [===============>..............] - ETA: 0s - loss: 0.2850 - mse: 191.1163
31/45 [===================>..........] - ETA: 0s - loss: 0.2818 - mse: 192.7129
37/45 [=======================>......] - ETA: 0s - loss: 0.2788 - mse: 192.8163
43/45 [===========================>..] - ETA: 0s - loss: 0.2734 - mse: 191.9709
45/45 [==============================] - 0s 9ms/step - loss: 0.2724 - mse: 191.6186

45/45 [==============================] - 1s 13ms/step - loss: 0.2724 - mse: 191.6186 - val_loss: 0.4875 - val_mse: 188.1811
Epoch 24/100

 1/45 [..............................] - ETA: 0s - loss: 0.2752 - mse: 198.0538
 7/45 [===>..........................] - ETA: 0s - loss: 0.2637 - mse: 195.0494
13/45 [=======>......................] - ETA: 0s - loss: 0.2621 - mse: 192.6499
19/45 [===========>..................] - ETA: 0s - loss: 0.2629 - mse: 191.6098
25/45 [===============>..............] - ETA: 0s - loss: 0.2628 - mse: 193.2768
31/45 [===================>..........] - ETA: 0s - loss: 0.2634 - mse: 191.9773
37/45 [=======================>......] - ETA: 0s - loss: 0.2614 - mse: 191.9275
43/45 [===========================>..] - ETA: 0s - loss: 0.2600 - mse: 191.7652
45/45 [==============================] - 0s 9ms/step - loss: 0.2599 - mse: 191.6186

45/45 [==============================] - 1s 13ms/step - loss: 0.2599 - mse: 191.6186 - val_loss: 0.3726 - val_mse: 188.1811
Epoch 25/100

 1/45 [..............................] - ETA: 0s - loss: 0.2591 - mse: 203.9521
 7/45 [===>..........................] - ETA: 0s - loss: 0.2664 - mse: 189.8635
13/45 [=======>......................] - ETA: 0s - loss: 0.2592 - mse: 188.1328
19/45 [===========>..................] - ETA: 0s - loss: 0.2537 - mse: 190.4170
25/45 [===============>..............] - ETA: 0s - loss: 0.2517 - mse: 191.1088
31/45 [===================>..........] - ETA: 0s - loss: 0.2448 - mse: 191.2669
37/45 [=======================>......] - ETA: 0s - loss: 0.2433 - mse: 192.3597
43/45 [===========================>..] - ETA: 0s - loss: 0.2404 - mse: 192.2387
45/45 [==============================] - 0s 9ms/step - loss: 0.2396 - mse: 191.6188

45/45 [==============================] - 1s 13ms/step - loss: 0.2396 - mse: 191.6188 - val_loss: 0.6150 - val_mse: 188.1813
Epoch 26/100

 1/45 [..............................] - ETA: 0s - loss: 0.2915 - mse: 184.2707
 7/45 [===>..........................] - ETA: 0s - loss: 0.3263 - mse: 189.6991
13/45 [=======>......................] - ETA: 0s - loss: 0.3201 - mse: 190.0042
19/45 [===========>..................] - ETA: 0s - loss: 0.3169 - mse: 192.3132
25/45 [===============>..............] - ETA: 0s - loss: 0.3151 - mse: 192.7925
31/45 [===================>..........] - ETA: 0s - loss: 0.3098 - mse: 191.4477
37/45 [=======================>......] - ETA: 0s - loss: 0.3107 - mse: 191.0546
43/45 [===========================>..] - ETA: 0s - loss: 0.3363 - mse: 191.7467
45/45 [==============================] - 0s 9ms/step - loss: 0.3385 - mse: 191.6187

45/45 [==============================] - 1s 13ms/step - loss: 0.3385 - mse: 191.6187 - val_loss: 0.6044 - val_mse: 188.1813
Epoch 27/100

 1/45 [..............................] - ETA: 0s - loss: 0.4852 - mse: 199.7695
 7/45 [===>..........................] - ETA: 0s - loss: 0.4462 - mse: 200.4563
13/45 [=======>......................] - ETA: 0s - loss: 0.4279 - mse: 194.7708
19/45 [===========>..................] - ETA: 0s - loss: 0.3885 - mse: 192.0728
25/45 [===============>..............] - ETA: 0s - loss: 0.3545 - mse: 190.9014
31/45 [===================>..........] - ETA: 0s - loss: 0.3282 - mse: 191.8837
37/45 [=======================>......] - ETA: 0s - loss: 0.3092 - mse: 192.2462
43/45 [===========================>..] - ETA: 0s - loss: 0.2988 - mse: 191.5410
45/45 [==============================] - 0s 9ms/step - loss: 0.2963 - mse: 191.6187

45/45 [==============================] - 1s 13ms/step - loss: 0.2963 - mse: 191.6187 - val_loss: 0.3901 - val_mse: 188.1813
Epoch 28/100

 1/45 [..............................] - ETA: 0s - loss: 0.2290 - mse: 197.7421
 7/45 [===>..........................] - ETA: 0s - loss: 0.2112 - mse: 186.9473
13/45 [=======>......................] - ETA: 0s - loss: 0.2154 - mse: 193.1032
19/45 [===========>..................] - ETA: 0s - loss: 0.2155 - mse: 191.9932
25/45 [===============>..............] - ETA: 0s - loss: 0.2121 - mse: 191.8202
31/45 [===================>..........] - ETA: 0s - loss: 0.2154 - mse: 191.6649
37/45 [=======================>......] - ETA: 0s - loss: 0.2138 - mse: 191.2767
43/45 [===========================>..] - ETA: 0s - loss: 0.2188 - mse: 191.1963
45/45 [==============================] - 0s 9ms/step - loss: 0.2185 - mse: 191.6189

45/45 [==============================] - 1s 13ms/step - loss: 0.2185 - mse: 191.6189 - val_loss: 0.3950 - val_mse: 188.1814
Epoch 29/100

 1/45 [..............................] - ETA: 0s - loss: 0.1614 - mse: 170.6444
 7/45 [===>..........................] - ETA: 0s - loss: 0.2323 - mse: 192.6649
13/45 [=======>......................] - ETA: 0s - loss: 0.2326 - mse: 190.3085
19/45 [===========>..................] - ETA: 0s - loss: 0.2282 - mse: 190.3735
25/45 [===============>..............] - ETA: 0s - loss: 0.2289 - mse: 190.2202
31/45 [===================>..........] - ETA: 0s - loss: 0.2233 - mse: 189.9227
37/45 [=======================>......] - ETA: 0s - loss: 0.2206 - mse: 191.5633
43/45 [===========================>..] - ETA: 0s - loss: 0.2170 - mse: 191.4536
45/45 [==============================] - 0s 9ms/step - loss: 0.2167 - mse: 191.6190

45/45 [==============================] - 1s 13ms/step - loss: 0.2167 - mse: 191.6190 - val_loss: 0.3393 - val_mse: 188.1814
Epoch 30/100

 1/45 [..............................] - ETA: 0s - loss: 0.2302 - mse: 210.2237
 7/45 [===>..........................] - ETA: 0s - loss: 0.2254 - mse: 197.6131
13/45 [=======>......................] - ETA: 0s - loss: 0.2160 - mse: 193.0094
19/45 [===========>..................] - ETA: 0s - loss: 0.2113 - mse: 191.4654
25/45 [===============>..............] - ETA: 0s - loss: 0.2063 - mse: 191.1707
31/45 [===================>..........] - ETA: 0s - loss: 0.2056 - mse: 191.2377
37/45 [=======================>......] - ETA: 0s - loss: 0.2051 - mse: 192.7028
43/45 [===========================>..] - ETA: 0s - loss: 0.2019 - mse: 192.1711
45/45 [==============================] - 0s 9ms/step - loss: 0.2009 - mse: 191.6190

45/45 [==============================] - 1s 13ms/step - loss: 0.2009 - mse: 191.6190 - val_loss: 0.3744 - val_mse: 188.1814
Epoch 31/100

 1/45 [..............................] - ETA: 0s - loss: 0.2054 - mse: 189.9487
 7/45 [===>..........................] - ETA: 0s - loss: 0.1813 - mse: 189.8674
13/45 [=======>......................] - ETA: 0s - loss: 0.1825 - mse: 191.3027
19/45 [===========>..................] - ETA: 0s - loss: 0.1865 - mse: 193.4529
25/45 [===============>..............] - ETA: 0s - loss: 0.1840 - mse: 191.9971
31/45 [===================>..........] - ETA: 0s - loss: 0.1791 - mse: 190.8340
37/45 [=======================>......] - ETA: 0s - loss: 0.1775 - mse: 191.8356
43/45 [===========================>..] - ETA: 0s - loss: 0.1773 - mse: 191.8960
45/45 [==============================] - 0s 9ms/step - loss: 0.1777 - mse: 191.6191

45/45 [==============================] - 1s 13ms/step - loss: 0.1777 - mse: 191.6191 - val_loss: 0.5258 - val_mse: 188.1815
Epoch 32/100

 1/45 [..............................] - ETA: 0s - loss: 0.1890 - mse: 195.2498
 7/45 [===>..........................] - ETA: 0s - loss: 0.2083 - mse: 193.6867
13/45 [=======>......................] - ETA: 0s - loss: 0.2045 - mse: 189.1117
19/45 [===========>..................] - ETA: 0s - loss: 0.2072 - mse: 192.0093
25/45 [===============>..............] - ETA: 0s - loss: 0.2052 - mse: 191.6552
31/45 [===================>..........] - ETA: 0s - loss: 0.2025 - mse: 191.8626
37/45 [=======================>......] - ETA: 0s - loss: 0.2017 - mse: 190.7924
43/45 [===========================>..] - ETA: 0s - loss: 0.2031 - mse: 192.0706
45/45 [==============================] - 0s 9ms/step - loss: 0.2020 - mse: 191.6192

45/45 [==============================] - 1s 13ms/step - loss: 0.2020 - mse: 191.6192 - val_loss: 0.3397 - val_mse: 188.1816
Epoch 33/100

 1/45 [..............................] - ETA: 0s - loss: 0.2187 - mse: 197.2387
 7/45 [===>..........................] - ETA: 0s - loss: 0.1960 - mse: 189.5639
13/45 [=======>......................] - ETA: 0s - loss: 0.2009 - mse: 189.3297
19/45 [===========>..................] - ETA: 0s - loss: 0.1959 - mse: 189.5715
25/45 [===============>..............] - ETA: 0s - loss: 0.1912 - mse: 191.9162
31/45 [===================>..........] - ETA: 0s - loss: 0.1907 - mse: 193.1625
37/45 [=======================>......] - ETA: 0s - loss: 0.1848 - mse: 192.4900
43/45 [===========================>..] - ETA: 0s - loss: 0.1830 - mse: 191.8060
45/45 [==============================] - 0s 9ms/step - loss: 0.1826 - mse: 191.6192

45/45 [==============================] - 1s 13ms/step - loss: 0.1826 - mse: 191.6192 - val_loss: 0.3358 - val_mse: 188.1816
Epoch 34/100

 1/45 [..............................] - ETA: 0s - loss: 0.1404 - mse: 208.3179
 7/45 [===>..........................] - ETA: 0s - loss: 0.1535 - mse: 192.0139
13/45 [=======>......................] - ETA: 0s - loss: 0.1723 - mse: 195.0387
19/45 [===========>..................] - ETA: 0s - loss: 0.1834 - mse: 196.3236
25/45 [===============>..............] - ETA: 0s - loss: 0.1833 - mse: 196.0091
31/45 [===================>..........] - ETA: 0s - loss: 0.1794 - mse: 194.9230
37/45 [=======================>......] - ETA: 0s - loss: 0.1779 - mse: 192.9571
43/45 [===========================>..] - ETA: 0s - loss: 0.1762 - mse: 192.0839
45/45 [==============================] - 0s 9ms/step - loss: 0.1761 - mse: 191.6193

45/45 [==============================] - 1s 13ms/step - loss: 0.1761 - mse: 191.6193 - val_loss: 0.3564 - val_mse: 188.1817
Epoch 35/100

 1/45 [..............................] - ETA: 0s - loss: 0.1550 - mse: 195.3087
 7/45 [===>..........................] - ETA: 0s - loss: 0.2506 - mse: 194.6199
13/45 [=======>......................] - ETA: 0s - loss: 0.2407 - mse: 196.4112
19/45 [===========>..................] - ETA: 0s - loss: 0.2286 - mse: 193.6074
25/45 [===============>..............] - ETA: 0s - loss: 0.2245 - mse: 194.6328
31/45 [===================>..........] - ETA: 0s - loss: 0.2154 - mse: 193.8954
37/45 [=======================>......] - ETA: 0s - loss: 0.2104 - mse: 192.3120
43/45 [===========================>..] - ETA: 0s - loss: 0.2049 - mse: 191.5743
45/45 [==============================] - 0s 9ms/step - loss: 0.2046 - mse: 191.6193

45/45 [==============================] - 1s 13ms/step - loss: 0.2046 - mse: 191.6193 - val_loss: 0.3843 - val_mse: 188.1817
Epoch 36/100

 1/45 [..............................] - ETA: 0s - loss: 0.1999 - mse: 204.6833
 7/45 [===>..........................] - ETA: 0s - loss: 0.1887 - mse: 188.5623
13/45 [=======>......................] - ETA: 0s - loss: 0.1826 - mse: 187.6042
19/45 [===========>..................] - ETA: 0s - loss: 0.1744 - mse: 188.3497
25/45 [===============>..............] - ETA: 0s - loss: 0.1735 - mse: 189.9545
31/45 [===================>..........] - ETA: 0s - loss: 0.1750 - mse: 191.7267
37/45 [=======================>......] - ETA: 0s - loss: 0.1742 - mse: 191.7616
43/45 [===========================>..] - ETA: 0s - loss: 0.1711 - mse: 191.6778
45/45 [==============================] - 0s 9ms/step - loss: 0.1710 - mse: 191.6193

45/45 [==============================] - 1s 13ms/step - loss: 0.1710 - mse: 191.6193 - val_loss: 0.3675 - val_mse: 188.1818
Epoch 37/100

 1/45 [..............................] - ETA: 0s - loss: 0.1558 - mse: 197.7657
 7/45 [===>..........................] - ETA: 0s - loss: 0.2027 - mse: 189.3232
13/45 [=======>......................] - ETA: 0s - loss: 0.2034 - mse: 193.8911
19/45 [===========>..................] - ETA: 0s - loss: 0.1930 - mse: 191.7599
25/45 [===============>..............] - ETA: 0s - loss: 0.1862 - mse: 191.3043
31/45 [===================>..........] - ETA: 0s - loss: 0.1823 - mse: 191.5540
37/45 [=======================>......] - ETA: 0s - loss: 0.1762 - mse: 191.0133
43/45 [===========================>..] - ETA: 0s - loss: 0.1753 - mse: 192.2101
45/45 [==============================] - 0s 9ms/step - loss: 0.1742 - mse: 191.6194

45/45 [==============================] - 1s 13ms/step - loss: 0.1742 - mse: 191.6194 - val_loss: 0.5049 - val_mse: 188.1819
Epoch 38/100

 1/45 [..............................] - ETA: 0s - loss: 0.1416 - mse: 212.1892
 7/45 [===>..........................] - ETA: 0s - loss: 0.1588 - mse: 196.5096
13/45 [=======>......................] - ETA: 0s - loss: 0.1586 - mse: 188.2905
19/45 [===========>..................] - ETA: 0s - loss: 0.1534 - mse: 192.7186
25/45 [===============>..............] - ETA: 0s - loss: 0.1523 - mse: 192.8619
31/45 [===================>..........] - ETA: 0s - loss: 0.1485 - mse: 190.9407
37/45 [=======================>......] - ETA: 0s - loss: 0.1510 - mse: 190.9938
43/45 [===========================>..] - ETA: 0s - loss: 0.1497 - mse: 191.9029
45/45 [==============================] - 0s 9ms/step - loss: 0.1497 - mse: 191.6194

45/45 [==============================] - 1s 13ms/step - loss: 0.1497 - mse: 191.6194 - val_loss: 0.3959 - val_mse: 188.1818
Epoch 39/100

 1/45 [..............................] - ETA: 0s - loss: 0.1365 - mse: 192.5854
 7/45 [===>..........................] - ETA: 0s - loss: 0.1710 - mse: 185.3857
13/45 [=======>......................] - ETA: 0s - loss: 0.1759 - mse: 191.2770
19/45 [===========>..................] - ETA: 0s - loss: 0.1767 - mse: 188.3114
25/45 [===============>..............] - ETA: 0s - loss: 0.1737 - mse: 190.2548
31/45 [===================>..........] - ETA: 0s - loss: 0.1689 - mse: 190.9335
37/45 [=======================>......] - ETA: 0s - loss: 0.1662 - mse: 191.1748
43/45 [===========================>..] - ETA: 0s - loss: 0.1626 - mse: 191.8500
45/45 [==============================] - 0s 9ms/step - loss: 0.1617 - mse: 191.6195

45/45 [==============================] - 1s 13ms/step - loss: 0.1617 - mse: 191.6195 - val_loss: 0.4430 - val_mse: 188.1818
Epoch 40/100

 1/45 [..............................] - ETA: 0s - loss: 0.1420 - mse: 205.9058
 7/45 [===>..........................] - ETA: 0s - loss: 0.1481 - mse: 200.2736
13/45 [=======>......................] - ETA: 0s - loss: 0.1446 - mse: 194.7260
19/45 [===========>..................] - ETA: 0s - loss: 0.1459 - mse: 193.1693
25/45 [===============>..............] - ETA: 0s - loss: 0.1448 - mse: 192.8251
31/45 [===================>..........] - ETA: 0s - loss: 0.1440 - mse: 192.0029
37/45 [=======================>......] - ETA: 0s - loss: 0.1461 - mse: 192.5750
43/45 [===========================>..] - ETA: 0s - loss: 0.1499 - mse: 191.8636
45/45 [==============================] - 0s 9ms/step - loss: 0.1503 - mse: 191.6195

45/45 [==============================] - 1s 13ms/step - loss: 0.1503 - mse: 191.6195 - val_loss: 0.8089 - val_mse: 188.1820
Epoch 41/100

 1/45 [..............................] - ETA: 0s - loss: 0.2184 - mse: 186.9111
 7/45 [===>..........................] - ETA: 0s - loss: 0.2717 - mse: 191.8644
13/45 [=======>......................] - ETA: 0s - loss: 0.2672 - mse: 192.2419
19/45 [===========>..................] - ETA: 0s - loss: 0.2557 - mse: 190.4369
25/45 [===============>..............] - ETA: 0s - loss: 0.2441 - mse: 191.6579
31/45 [===================>..........] - ETA: 0s - loss: 0.2302 - mse: 191.4807
37/45 [=======================>......] - ETA: 0s - loss: 0.2201 - mse: 192.3035
43/45 [===========================>..] - ETA: 0s - loss: 0.2122 - mse: 191.9169
45/45 [==============================] - 0s 9ms/step - loss: 0.2114 - mse: 191.6194

45/45 [==============================] - 1s 13ms/step - loss: 0.2114 - mse: 191.6194 - val_loss: 0.4792 - val_mse: 188.1819
Epoch 42/100

 1/45 [..............................] - ETA: 0s - loss: 0.2353 - mse: 190.3289
 7/45 [===>..........................] - ETA: 0s - loss: 0.2412 - mse: 187.9965
13/45 [=======>......................] - ETA: 0s - loss: 0.2087 - mse: 189.1921
17/45 [==========>...................] - ETA: 0s - loss: 0.2040 - mse: 188.2867
22/45 [=============>................] - ETA: 0s - loss: 0.1956 - mse: 186.5908
28/45 [=================>............] - ETA: 0s - loss: 0.1868 - mse: 189.6054
34/45 [=====================>........] - ETA: 0s - loss: 0.1818 - mse: 190.8180
40/45 [=========================>....] - ETA: 0s - loss: 0.1760 - mse: 190.7023
45/45 [==============================] - 0s 10ms/step - loss: 0.1737 - mse: 191.6195

45/45 [==============================] - 1s 14ms/step - loss: 0.1737 - mse: 191.6195 - val_loss: 0.4758 - val_mse: 188.1819
Epoch 43/100

 1/45 [..............................] - ETA: 0s - loss: 0.1655 - mse: 170.1883
 7/45 [===>..........................] - ETA: 0s - loss: 0.1524 - mse: 185.6213
13/45 [=======>......................] - ETA: 0s - loss: 0.1591 - mse: 190.5605
19/45 [===========>..................] - ETA: 0s - loss: 0.1562 - mse: 192.4100
24/45 [===============>..............] - ETA: 0s - loss: 0.1509 - mse: 191.6441
30/45 [===================>..........] - ETA: 0s - loss: 0.1482 - mse: 192.4506
35/45 [======================>.......] - ETA: 0s - loss: 0.1454 - mse: 192.9021
41/45 [==========================>...] - ETA: 0s - loss: 0.1422 - mse: 191.7579
45/45 [==============================] - 0s 10ms/step - loss: 0.1414 - mse: 191.6196

45/45 [==============================] - 1s 13ms/step - loss: 0.1414 - mse: 191.6196 - val_loss: 0.3771 - val_mse: 188.1819
Epoch 44/100

 1/45 [..............................] - ETA: 0s - loss: 0.1673 - mse: 190.3597
 7/45 [===>..........................] - ETA: 0s - loss: 0.1548 - mse: 192.0915
13/45 [=======>......................] - ETA: 0s - loss: 0.1449 - mse: 191.8557
19/45 [===========>..................] - ETA: 0s - loss: 0.1411 - mse: 191.5429
25/45 [===============>..............] - ETA: 0s - loss: 0.1399 - mse: 189.3132
31/45 [===================>..........] - ETA: 0s - loss: 0.1420 - mse: 189.9719
37/45 [=======================>......] - ETA: 0s - loss: 0.1418 - mse: 190.1968
43/45 [===========================>..] - ETA: 0s - loss: 0.1432 - mse: 191.8114
45/45 [==============================] - 0s 9ms/step - loss: 0.1419 - mse: 191.6196

45/45 [==============================] - 1s 13ms/step - loss: 0.1419 - mse: 191.6196 - val_loss: 0.3431 - val_mse: 188.1819
Epoch 45/100

 1/45 [..............................] - ETA: 0s - loss: 0.1907 - mse: 203.0809
 7/45 [===>..........................] - ETA: 0s - loss: 0.1702 - mse: 193.7833
13/45 [=======>......................] - ETA: 0s - loss: 0.1560 - mse: 196.4265
19/45 [===========>..................] - ETA: 0s - loss: 0.1530 - mse: 193.3366
25/45 [===============>..............] - ETA: 0s - loss: 0.1561 - mse: 195.1322
31/45 [===================>..........] - ETA: 0s - loss: 0.1560 - mse: 194.2972
37/45 [=======================>......] - ETA: 0s - loss: 0.1511 - mse: 192.7629
43/45 [===========================>..] - ETA: 0s - loss: 0.1472 - mse: 192.0005
45/45 [==============================] - 0s 9ms/step - loss: 0.1465 - mse: 191.6196

45/45 [==============================] - 1s 13ms/step - loss: 0.1465 - mse: 191.6196 - val_loss: 0.4377 - val_mse: 188.1820
Epoch 46/100

 1/45 [..............................] - ETA: 0s - loss: 0.1289 - mse: 184.6962
 7/45 [===>..........................] - ETA: 0s - loss: 0.1538 - mse: 190.0039
13/45 [=======>......................] - ETA: 0s - loss: 0.1456 - mse: 187.0128
19/45 [===========>..................] - ETA: 0s - loss: 0.1395 - mse: 190.3593
25/45 [===============>..............] - ETA: 0s - loss: 0.1377 - mse: 191.9439
31/45 [===================>..........] - ETA: 0s - loss: 0.1361 - mse: 192.5191
37/45 [=======================>......] - ETA: 0s - loss: 0.1378 - mse: 191.6652
43/45 [===========================>..] - ETA: 0s - loss: 0.1364 - mse: 191.8476
45/45 [==============================] - 0s 9ms/step - loss: 0.1360 - mse: 191.6196

45/45 [==============================] - 1s 13ms/step - loss: 0.1360 - mse: 191.6196 - val_loss: 0.2990 - val_mse: 188.1820
Epoch 47/100

 1/45 [..............................] - ETA: 0s - loss: 0.1718 - mse: 199.6401
 7/45 [===>..........................] - ETA: 0s - loss: 0.1575 - mse: 204.0167
13/45 [=======>......................] - ETA: 0s - loss: 0.1538 - mse: 201.2375
19/45 [===========>..................] - ETA: 0s - loss: 0.1491 - mse: 195.3493
25/45 [===============>..............] - ETA: 0s - loss: 0.1446 - mse: 194.9294
31/45 [===================>..........] - ETA: 0s - loss: 0.1413 - mse: 193.6255
37/45 [=======================>......] - ETA: 0s - loss: 0.1399 - mse: 193.3731
43/45 [===========================>..] - ETA: 0s - loss: 0.1379 - mse: 191.8501
45/45 [==============================] - 0s 9ms/step - loss: 0.1376 - mse: 191.6196

45/45 [==============================] - 1s 13ms/step - loss: 0.1376 - mse: 191.6196 - val_loss: 0.4316 - val_mse: 188.1820
Epoch 48/100

 1/45 [..............................] - ETA: 0s - loss: 0.1718 - mse: 208.0406
 7/45 [===>..........................] - ETA: 0s - loss: 0.2000 - mse: 193.1731
13/45 [=======>......................] - ETA: 0s - loss: 0.1817 - mse: 195.7581
19/45 [===========>..................] - ETA: 0s - loss: 0.1670 - mse: 190.9676
25/45 [===============>..............] - ETA: 0s - loss: 0.1595 - mse: 190.7294
31/45 [===================>..........] - ETA: 0s - loss: 0.1561 - mse: 191.1372
37/45 [=======================>......] - ETA: 0s - loss: 0.1483 - mse: 191.4752
43/45 [===========================>..] - ETA: 0s - loss: 0.1425 - mse: 191.1978
45/45 [==============================] - 0s 9ms/step - loss: 0.1418 - mse: 191.6197

45/45 [==============================] - 1s 13ms/step - loss: 0.1418 - mse: 191.6197 - val_loss: 0.4974 - val_mse: 188.1821
Epoch 49/100

 1/45 [..............................] - ETA: 0s - loss: 0.1325 - mse: 205.3611
 7/45 [===>..........................] - ETA: 0s - loss: 0.1347 - mse: 196.8982
13/45 [=======>......................] - ETA: 0s - loss: 0.1208 - mse: 193.8220
19/45 [===========>..................] - ETA: 0s - loss: 0.1154 - mse: 191.8298
25/45 [===============>..............] - ETA: 0s - loss: 0.1141 - mse: 191.0056
31/45 [===================>..........] - ETA: 0s - loss: 0.1140 - mse: 190.7607
37/45 [=======================>......] - ETA: 0s - loss: 0.1146 - mse: 190.8708
43/45 [===========================>..] - ETA: 0s - loss: 0.1182 - mse: 191.7868
45/45 [==============================] - 0s 9ms/step - loss: 0.1187 - mse: 191.6197

45/45 [==============================] - 1s 13ms/step - loss: 0.1187 - mse: 191.6197 - val_loss: 0.4314 - val_mse: 188.1820
Epoch 50/100

 1/45 [..............................] - ETA: 0s - loss: 0.1003 - mse: 195.3806
 7/45 [===>..........................] - ETA: 0s - loss: 0.0968 - mse: 184.2928
13/45 [=======>......................] - ETA: 0s - loss: 0.1023 - mse: 186.5368
19/45 [===========>..................] - ETA: 0s - loss: 0.1025 - mse: 187.0614
25/45 [===============>..............] - ETA: 0s - loss: 0.1055 - mse: 188.5708
31/45 [===================>..........] - ETA: 0s - loss: 0.1104 - mse: 190.5189
37/45 [=======================>......] - ETA: 0s - loss: 0.1100 - mse: 191.6153
43/45 [===========================>..] - ETA: 0s - loss: 0.1102 - mse: 191.6814
45/45 [==============================] - 0s 9ms/step - loss: 0.1105 - mse: 191.6197

45/45 [==============================] - 1s 13ms/step - loss: 0.1105 - mse: 191.6197 - val_loss: 0.3636 - val_mse: 188.1821
Epoch 51/100

 1/45 [..............................] - ETA: 0s - loss: 0.0811 - mse: 184.7833
 7/45 [===>..........................] - ETA: 0s - loss: 0.1242 - mse: 193.7289
13/45 [=======>......................] - ETA: 0s - loss: 0.1313 - mse: 193.9162
19/45 [===========>..................] - ETA: 0s - loss: 0.1337 - mse: 194.9740
25/45 [===============>..............] - ETA: 0s - loss: 0.1318 - mse: 193.6328
31/45 [===================>..........] - ETA: 0s - loss: 0.1339 - mse: 194.9135
37/45 [=======================>......] - ETA: 0s - loss: 0.1306 - mse: 193.8683
43/45 [===========================>..] - ETA: 0s - loss: 0.1282 - mse: 192.0415
45/45 [==============================] - 0s 9ms/step - loss: 0.1273 - mse: 191.6198

45/45 [==============================] - 1s 13ms/step - loss: 0.1273 - mse: 191.6198 - val_loss: 0.4202 - val_mse: 188.1821
Epoch 52/100

 1/45 [..............................] - ETA: 0s - loss: 0.1177 - mse: 200.9171
 7/45 [===>..........................] - ETA: 0s - loss: 0.1656 - mse: 187.2873
13/45 [=======>......................] - ETA: 0s - loss: 0.1579 - mse: 190.8466
19/45 [===========>..................] - ETA: 0s - loss: 0.1471 - mse: 191.7868
25/45 [===============>..............] - ETA: 0s - loss: 0.1405 - mse: 191.9528
31/45 [===================>..........] - ETA: 0s - loss: 0.1301 - mse: 190.9701
37/45 [=======================>......] - ETA: 0s - loss: 0.1259 - mse: 191.0447
43/45 [===========================>..] - ETA: 0s - loss: 0.1231 - mse: 191.5137
45/45 [==============================] - 0s 9ms/step - loss: 0.1235 - mse: 191.6198

45/45 [==============================] - 1s 13ms/step - loss: 0.1235 - mse: 191.6198 - val_loss: 0.3872 - val_mse: 188.1820
Epoch 53/100

 1/45 [..............................] - ETA: 0s - loss: 0.1001 - mse: 184.7065
 7/45 [===>..........................] - ETA: 0s - loss: 0.0932 - mse: 190.0456
13/45 [=======>......................] - ETA: 0s - loss: 0.0911 - mse: 191.0709
19/45 [===========>..................] - ETA: 0s - loss: 0.0929 - mse: 193.9974
25/45 [===============>..............] - ETA: 0s - loss: 0.0936 - mse: 192.7953
31/45 [===================>..........] - ETA: 0s - loss: 0.0916 - mse: 191.6589
37/45 [=======================>......] - ETA: 0s - loss: 0.0908 - mse: 192.0062
43/45 [===========================>..] - ETA: 0s - loss: 0.0908 - mse: 191.5423
45/45 [==============================] - 0s 9ms/step - loss: 0.0903 - mse: 191.6199

45/45 [==============================] - 1s 13ms/step - loss: 0.0903 - mse: 191.6199 - val_loss: 0.3934 - val_mse: 188.1821
Epoch 54/100

 1/45 [..............................] - ETA: 0s - loss: 0.0847 - mse: 200.4387
 7/45 [===>..........................] - ETA: 0s - loss: 0.0844 - mse: 191.4139
13/45 [=======>......................] - ETA: 0s - loss: 0.0816 - mse: 193.0540
18/45 [===========>..................] - ETA: 0s - loss: 0.0822 - mse: 192.8708
23/45 [==============>...............] - ETA: 0s - loss: 0.0822 - mse: 192.7137
29/45 [==================>...........] - ETA: 0s - loss: 0.0821 - mse: 192.7004
35/45 [======================>.......] - ETA: 0s - loss: 0.0829 - mse: 191.2491
41/45 [==========================>...] - ETA: 0s - loss: 0.0823 - mse: 192.0976
45/45 [==============================] - 0s 10ms/step - loss: 0.0822 - mse: 191.6199

45/45 [==============================] - 1s 13ms/step - loss: 0.0822 - mse: 191.6199 - val_loss: 0.3402 - val_mse: 188.1822
Epoch 55/100

 1/45 [..............................] - ETA: 0s - loss: 0.0807 - mse: 195.5312
 7/45 [===>..........................] - ETA: 0s - loss: 0.0973 - mse: 194.6687
13/45 [=======>......................] - ETA: 0s - loss: 0.0995 - mse: 194.7145
19/45 [===========>..................] - ETA: 0s - loss: 0.1010 - mse: 191.7801
25/45 [===============>..............] - ETA: 0s - loss: 0.0987 - mse: 190.2773
31/45 [===================>..........] - ETA: 0s - loss: 0.0979 - mse: 191.3826
37/45 [=======================>......] - ETA: 0s - loss: 0.0985 - mse: 191.9323
43/45 [===========================>..] - ETA: 0s - loss: 0.0970 - mse: 191.9485
45/45 [==============================] - 0s 9ms/step - loss: 0.0967 - mse: 191.6199

45/45 [==============================] - 1s 13ms/step - loss: 0.0967 - mse: 191.6199 - val_loss: 0.3904 - val_mse: 188.1822
Epoch 56/100

 1/45 [..............................] - ETA: 0s - loss: 0.0822 - mse: 191.6879
 6/45 [===>..........................] - ETA: 0s - loss: 0.1011 - mse: 194.9012
12/45 [=======>......................] - ETA: 0s - loss: 0.1075 - mse: 193.5113
18/45 [===========>..................] - ETA: 0s - loss: 0.1094 - mse: 193.6347
24/45 [===============>..............] - ETA: 0s - loss: 0.1071 - mse: 191.1909
30/45 [===================>..........] - ETA: 0s - loss: 0.1057 - mse: 191.1997
36/45 [=======================>......] - ETA: 0s - loss: 0.1029 - mse: 190.7030
42/45 [===========================>..] - ETA: 0s - loss: 0.1015 - mse: 190.7322
45/45 [==============================] - 0s 9ms/step - loss: 0.1006 - mse: 191.6199

45/45 [==============================] - 1s 13ms/step - loss: 0.1006 - mse: 191.6199 - val_loss: 0.3247 - val_mse: 188.1822
Epoch 57/100

 1/45 [..............................] - ETA: 0s - loss: 0.0829 - mse: 204.3448
 7/45 [===>..........................] - ETA: 0s - loss: 0.1153 - mse: 198.1329
13/45 [=======>......................] - ETA: 0s - loss: 0.1178 - mse: 197.3944
19/45 [===========>..................] - ETA: 0s - loss: 0.1123 - mse: 194.5556
25/45 [===============>..............] - ETA: 0s - loss: 0.1093 - mse: 192.5372
31/45 [===================>..........] - ETA: 0s - loss: 0.1146 - mse: 192.4046
37/45 [=======================>......] - ETA: 0s - loss: 0.1165 - mse: 191.1576
43/45 [===========================>..] - ETA: 0s - loss: 0.1184 - mse: 191.5688
45/45 [==============================] - 0s 9ms/step - loss: 0.1177 - mse: 191.6199

45/45 [==============================] - 1s 13ms/step - loss: 0.1177 - mse: 191.6199 - val_loss: 0.3836 - val_mse: 188.1822
Epoch 58/100

 1/45 [..............................] - ETA: 0s - loss: 0.1368 - mse: 201.2513
 7/45 [===>..........................] - ETA: 0s - loss: 0.1538 - mse: 196.2440
13/45 [=======>......................] - ETA: 0s - loss: 0.1401 - mse: 193.7499
19/45 [===========>..................] - ETA: 0s - loss: 0.1285 - mse: 190.0541
25/45 [===============>..............] - ETA: 0s - loss: 0.1181 - mse: 189.7317
31/45 [===================>..........] - ETA: 0s - loss: 0.1092 - mse: 189.8303
37/45 [=======================>......] - ETA: 0s - loss: 0.1051 - mse: 191.0281
43/45 [===========================>..] - ETA: 0s - loss: 0.1019 - mse: 191.8792
45/45 [==============================] - 0s 9ms/step - loss: 0.1010 - mse: 191.6199

45/45 [==============================] - 1s 13ms/step - loss: 0.1010 - mse: 191.6199 - val_loss: 0.4083 - val_mse: 188.1822
Epoch 59/100

 1/45 [..............................] - ETA: 0s - loss: 0.0929 - mse: 205.0138
 7/45 [===>..........................] - ETA: 0s - loss: 0.2264 - mse: 191.8331
13/45 [=======>......................] - ETA: 0s - loss: 0.2479 - mse: 192.0556
19/45 [===========>..................] - ETA: 0s - loss: 0.2409 - mse: 192.4715
25/45 [===============>..............] - ETA: 0s - loss: 0.2272 - mse: 192.8642
31/45 [===================>..........] - ETA: 0s - loss: 0.2196 - mse: 192.4386
37/45 [=======================>......] - ETA: 0s - loss: 0.2094 - mse: 191.1742
43/45 [===========================>..] - ETA: 0s - loss: 0.2002 - mse: 191.4626
45/45 [==============================] - 0s 9ms/step - loss: 0.1969 - mse: 191.6198

45/45 [==============================] - 1s 13ms/step - loss: 0.1969 - mse: 191.6198 - val_loss: 0.5646 - val_mse: 188.1821
Epoch 60/100

 1/45 [..............................] - ETA: 0s - loss: 0.1448 - mse: 200.2666
 7/45 [===>..........................] - ETA: 0s - loss: 0.1691 - mse: 195.3044
13/45 [=======>......................] - ETA: 0s - loss: 0.1652 - mse: 194.2458
19/45 [===========>..................] - ETA: 0s - loss: 0.1620 - mse: 193.8427
25/45 [===============>..............] - ETA: 0s - loss: 0.1571 - mse: 193.0431
31/45 [===================>..........] - ETA: 0s - loss: 0.1509 - mse: 193.3742
37/45 [=======================>......] - ETA: 0s - loss: 0.1469 - mse: 193.5238
43/45 [===========================>..] - ETA: 0s - loss: 0.1390 - mse: 191.8753
45/45 [==============================] - 0s 9ms/step - loss: 0.1378 - mse: 191.6199

45/45 [==============================] - 1s 13ms/step - loss: 0.1378 - mse: 191.6199 - val_loss: 0.4402 - val_mse: 188.1822
Epoch 61/100

 1/45 [..............................] - ETA: 0s - loss: 0.0888 - mse: 208.3459
 7/45 [===>..........................] - ETA: 0s - loss: 0.1035 - mse: 194.2481
13/45 [=======>......................] - ETA: 0s - loss: 0.0941 - mse: 192.3836
19/45 [===========>..................] - ETA: 0s - loss: 0.0928 - mse: 190.6156
25/45 [===============>..............] - ETA: 0s - loss: 0.0880 - mse: 191.5553
31/45 [===================>..........] - ETA: 0s - loss: 0.0868 - mse: 191.1815
37/45 [=======================>......] - ETA: 0s - loss: 0.0884 - mse: 192.0190
43/45 [===========================>..] - ETA: 0s - loss: 0.0870 - mse: 191.7218
45/45 [==============================] - 0s 9ms/step - loss: 0.0871 - mse: 191.6200

45/45 [==============================] - 1s 13ms/step - loss: 0.0871 - mse: 191.6200 - val_loss: 0.3373 - val_mse: 188.1822
Epoch 62/100

 1/45 [..............................] - ETA: 0s - loss: 0.0786 - mse: 191.2205
 7/45 [===>..........................] - ETA: 0s - loss: 0.0929 - mse: 191.9469
13/45 [=======>......................] - ETA: 0s - loss: 0.0875 - mse: 190.8019
19/45 [===========>..................] - ETA: 0s - loss: 0.0894 - mse: 193.4046
25/45 [===============>..............] - ETA: 0s - loss: 0.0862 - mse: 193.4135
31/45 [===================>..........] - ETA: 0s - loss: 0.0833 - mse: 192.3284
37/45 [=======================>......] - ETA: 0s - loss: 0.0807 - mse: 192.2428
43/45 [===========================>..] - ETA: 0s - loss: 0.0782 - mse: 192.2820
45/45 [==============================] - 0s 9ms/step - loss: 0.0777 - mse: 191.6200

45/45 [==============================] - 1s 13ms/step - loss: 0.0777 - mse: 191.6200 - val_loss: 0.4509 - val_mse: 188.1823
Epoch 63/100

 1/45 [..............................] - ETA: 0s - loss: 0.0719 - mse: 186.3722
 7/45 [===>..........................] - ETA: 0s - loss: 0.0710 - mse: 191.8350
13/45 [=======>......................] - ETA: 0s - loss: 0.0678 - mse: 190.6787
19/45 [===========>..................] - ETA: 0s - loss: 0.0664 - mse: 190.2422
25/45 [===============>..............] - ETA: 0s - loss: 0.0641 - mse: 189.4435
31/45 [===================>..........] - ETA: 0s - loss: 0.0646 - mse: 191.4480
37/45 [=======================>......] - ETA: 0s - loss: 0.0639 - mse: 191.4856
43/45 [===========================>..] - ETA: 0s - loss: 0.0650 - mse: 191.9978
45/45 [==============================] - 0s 9ms/step - loss: 0.0647 - mse: 191.6201

45/45 [==============================] - 1s 13ms/step - loss: 0.0647 - mse: 191.6201 - val_loss: 0.3157 - val_mse: 188.1823
Epoch 64/100

 1/45 [..............................] - ETA: 0s - loss: 0.0436 - mse: 175.5747
 7/45 [===>..........................] - ETA: 0s - loss: 0.0752 - mse: 185.1206
13/45 [=======>......................] - ETA: 0s - loss: 0.0860 - mse: 187.9582
19/45 [===========>..................] - ETA: 0s - loss: 0.0922 - mse: 188.9747
25/45 [===============>..............] - ETA: 0s - loss: 0.1054 - mse: 189.7372
31/45 [===================>..........] - ETA: 0s - loss: 0.1064 - mse: 191.0664
37/45 [=======================>......] - ETA: 0s - loss: 0.1039 - mse: 192.2046
43/45 [===========================>..] - ETA: 0s - loss: 0.1016 - mse: 191.9455
45/45 [==============================] - 0s 9ms/step - loss: 0.1007 - mse: 191.6200

45/45 [==============================] - 1s 13ms/step - loss: 0.1007 - mse: 191.6200 - val_loss: 0.3889 - val_mse: 188.1823
Epoch 65/100

 1/45 [..............................] - ETA: 0s - loss: 0.1536 - mse: 171.3434
 7/45 [===>..........................] - ETA: 0s - loss: 0.1100 - mse: 181.3282
13/45 [=======>......................] - ETA: 0s - loss: 0.1079 - mse: 190.3720
19/45 [===========>..................] - ETA: 0s - loss: 0.0996 - mse: 190.4078
25/45 [===============>..............] - ETA: 0s - loss: 0.0975 - mse: 191.8460
31/45 [===================>..........] - ETA: 0s - loss: 0.0996 - mse: 191.8905
37/45 [=======================>......] - ETA: 0s - loss: 0.0995 - mse: 191.4269
43/45 [===========================>..] - ETA: 0s - loss: 0.0982 - mse: 191.1192
45/45 [==============================] - 0s 9ms/step - loss: 0.0977 - mse: 191.6200

45/45 [==============================] - 1s 13ms/step - loss: 0.0977 - mse: 191.6200 - val_loss: 0.5342 - val_mse: 188.1823
Epoch 66/100

 1/45 [..............................] - ETA: 0s - loss: 0.1103 - mse: 176.9072
 7/45 [===>..........................] - ETA: 0s - loss: 0.0862 - mse: 185.7008
13/45 [=======>......................] - ETA: 0s - loss: 0.0866 - mse: 192.3314
19/45 [===========>..................] - ETA: 0s - loss: 0.0864 - mse: 189.9344
23/45 [==============>...............] - ETA: 0s - loss: 0.0858 - mse: 190.0876
28/45 [=================>............] - ETA: 0s - loss: 0.0814 - mse: 191.0081
34/45 [=====================>........] - ETA: 0s - loss: 0.0778 - mse: 189.2885
40/45 [=========================>....] - ETA: 0s - loss: 0.0748 - mse: 190.0905
45/45 [==============================] - 0s 10ms/step - loss: 0.0744 - mse: 191.6201

45/45 [==============================] - 1s 13ms/step - loss: 0.0744 - mse: 191.6201 - val_loss: 0.5076 - val_mse: 188.1823
Epoch 67/100

 1/45 [..............................] - ETA: 0s - loss: 0.0715 - mse: 186.3772
 7/45 [===>..........................] - ETA: 0s - loss: 0.1282 - mse: 192.5359
13/45 [=======>......................] - ETA: 0s - loss: 0.1064 - mse: 190.8953
19/45 [===========>..................] - ETA: 0s - loss: 0.1035 - mse: 188.4270
25/45 [===============>..............] - ETA: 0s - loss: 0.1034 - mse: 191.3571
31/45 [===================>..........] - ETA: 0s - loss: 0.0989 - mse: 189.8396
37/45 [=======================>......] - ETA: 0s - loss: 0.0940 - mse: 190.7831
43/45 [===========================>..] - ETA: 0s - loss: 0.0901 - mse: 191.4533
45/45 [==============================] - 0s 9ms/step - loss: 0.0892 - mse: 191.6201

45/45 [==============================] - 1s 13ms/step - loss: 0.0892 - mse: 191.6201 - val_loss: 0.3681 - val_mse: 188.1823
Epoch 68/100

 1/45 [..............................] - ETA: 0s - loss: 0.0571 - mse: 199.0520
 7/45 [===>..........................] - ETA: 0s - loss: 0.0805 - mse: 188.4384
13/45 [=======>......................] - ETA: 0s - loss: 0.0804 - mse: 190.6627
19/45 [===========>..................] - ETA: 0s - loss: 0.0754 - mse: 192.8739
25/45 [===============>..............] - ETA: 0s - loss: 0.0737 - mse: 191.1496
31/45 [===================>..........] - ETA: 0s - loss: 0.0700 - mse: 191.9443
37/45 [=======================>......] - ETA: 0s - loss: 0.0667 - mse: 189.5903
43/45 [===========================>..] - ETA: 0s - loss: 0.0660 - mse: 191.0830
45/45 [==============================] - 0s 9ms/step - loss: 0.0658 - mse: 191.6201

45/45 [==============================] - 1s 13ms/step - loss: 0.0658 - mse: 191.6201 - val_loss: 0.5225 - val_mse: 188.1823
Epoch 69/100

 1/45 [..............................] - ETA: 0s - loss: 0.0617 - mse: 183.4806
 7/45 [===>..........................] - ETA: 0s - loss: 0.0996 - mse: 188.0247
13/45 [=======>......................] - ETA: 0s - loss: 0.0850 - mse: 194.2108
19/45 [===========>..................] - ETA: 0s - loss: 0.0814 - mse: 191.2670
25/45 [===============>..............] - ETA: 0s - loss: 0.0822 - mse: 190.5737
31/45 [===================>..........] - ETA: 0s - loss: 0.0793 - mse: 191.1747
37/45 [=======================>......] - ETA: 0s - loss: 0.0774 - mse: 190.7536
43/45 [===========================>..] - ETA: 0s - loss: 0.0742 - mse: 191.2786
45/45 [==============================] - 0s 9ms/step - loss: 0.0739 - mse: 191.6201

45/45 [==============================] - 1s 13ms/step - loss: 0.0739 - mse: 191.6201 - val_loss: 0.3942 - val_mse: 188.1824
Epoch 70/100

 1/45 [..............................] - ETA: 0s - loss: 0.0397 - mse: 198.6603
 7/45 [===>..........................] - ETA: 0s - loss: 0.0639 - mse: 196.8451
13/45 [=======>......................] - ETA: 0s - loss: 0.0636 - mse: 191.1231
19/45 [===========>..................] - ETA: 0s - loss: 0.0602 - mse: 191.7491
25/45 [===============>..............] - ETA: 0s - loss: 0.0600 - mse: 189.7147
31/45 [===================>..........] - ETA: 0s - loss: 0.0580 - mse: 189.4081
37/45 [=======================>......] - ETA: 0s - loss: 0.0576 - mse: 191.3753
43/45 [===========================>..] - ETA: 0s - loss: 0.0561 - mse: 191.5593
45/45 [==============================] - 0s 9ms/step - loss: 0.0581 - mse: 191.6202

45/45 [==============================] - 1s 13ms/step - loss: 0.0581 - mse: 191.6202 - val_loss: 0.3883 - val_mse: 188.1823
Epoch 71/100

 1/45 [..............................] - ETA: 0s - loss: 0.0724 - mse: 199.6199
 7/45 [===>..........................] - ETA: 0s - loss: 0.0688 - mse: 189.0864
13/45 [=======>......................] - ETA: 0s - loss: 0.0607 - mse: 190.6768
19/45 [===========>..................] - ETA: 0s - loss: 0.0553 - mse: 188.7604
25/45 [===============>..............] - ETA: 0s - loss: 0.0531 - mse: 188.6023
31/45 [===================>..........] - ETA: 0s - loss: 0.0536 - mse: 189.7382
37/45 [=======================>......] - ETA: 0s - loss: 0.0543 - mse: 190.3054
43/45 [===========================>..] - ETA: 0s - loss: 0.0559 - mse: 191.8895
45/45 [==============================] - 0s 9ms/step - loss: 0.0556 - mse: 191.6202

45/45 [==============================] - 1s 13ms/step - loss: 0.0556 - mse: 191.6202 - val_loss: 0.3170 - val_mse: 188.1823
Epoch 72/100

 1/45 [..............................] - ETA: 0s - loss: 0.0428 - mse: 196.3841
 7/45 [===>..........................] - ETA: 0s - loss: 0.0546 - mse: 194.7511
13/45 [=======>......................] - ETA: 0s - loss: 0.0498 - mse: 190.4425
19/45 [===========>..................] - ETA: 0s - loss: 0.0488 - mse: 189.2621
25/45 [===============>..............] - ETA: 0s - loss: 0.0477 - mse: 188.7975
31/45 [===================>..........] - ETA: 0s - loss: 0.0472 - mse: 188.7091
37/45 [=======================>......] - ETA: 0s - loss: 0.0497 - mse: 191.0120
43/45 [===========================>..] - ETA: 0s - loss: 0.0505 - mse: 191.1744
45/45 [==============================] - 0s 10ms/step - loss: 0.0507 - mse: 191.6202

45/45 [==============================] - 1s 13ms/step - loss: 0.0507 - mse: 191.6202 - val_loss: 0.5693 - val_mse: 188.1824
Epoch 73/100

 1/45 [..............................] - ETA: 0s - loss: 0.0528 - mse: 207.4344
 7/45 [===>..........................] - ETA: 0s - loss: 0.0690 - mse: 190.6323
13/45 [=======>......................] - ETA: 0s - loss: 0.0801 - mse: 187.6682
19/45 [===========>..................] - ETA: 0s - loss: 0.0782 - mse: 187.5242
25/45 [===============>..............] - ETA: 0s - loss: 0.0774 - mse: 189.4565
31/45 [===================>..........] - ETA: 0s - loss: 0.0753 - mse: 190.7064
37/45 [=======================>......] - ETA: 0s - loss: 0.0772 - mse: 190.8649
43/45 [===========================>..] - ETA: 0s - loss: 0.0773 - mse: 191.6743
45/45 [==============================] - 0s 9ms/step - loss: 0.0763 - mse: 191.6201

45/45 [==============================] - 1s 13ms/step - loss: 0.0763 - mse: 191.6201 - val_loss: 0.5473 - val_mse: 188.1824
Epoch 74/100

 1/45 [..............................] - ETA: 0s - loss: 0.0591 - mse: 175.0314
 7/45 [===>..........................] - ETA: 0s - loss: 0.0809 - mse: 191.4498
13/45 [=======>......................] - ETA: 0s - loss: 0.0844 - mse: 191.6449
19/45 [===========>..................] - ETA: 0s - loss: 0.0785 - mse: 192.4337
25/45 [===============>..............] - ETA: 0s - loss: 0.0746 - mse: 191.9448
31/45 [===================>..........] - ETA: 0s - loss: 0.0743 - mse: 193.2831
37/45 [=======================>......] - ETA: 0s - loss: 0.0710 - mse: 191.6253
43/45 [===========================>..] - ETA: 0s - loss: 0.0685 - mse: 191.4268
45/45 [==============================] - 0s 9ms/step - loss: 0.0682 - mse: 191.6202

45/45 [==============================] - 1s 13ms/step - loss: 0.0682 - mse: 191.6202 - val_loss: 0.4041 - val_mse: 188.1824
Epoch 75/100

 1/45 [..............................] - ETA: 0s - loss: 0.0477 - mse: 196.4881
 7/45 [===>..........................] - ETA: 0s - loss: 0.1075 - mse: 188.4415
13/45 [=======>......................] - ETA: 0s - loss: 0.1017 - mse: 189.8352
19/45 [===========>..................] - ETA: 0s - loss: 0.0981 - mse: 191.1264
25/45 [===============>..............] - ETA: 0s - loss: 0.0932 - mse: 190.8456
31/45 [===================>..........] - ETA: 0s - loss: 0.0903 - mse: 190.7800
37/45 [=======================>......] - ETA: 0s - loss: 0.0850 - mse: 190.4297
43/45 [===========================>..] - ETA: 0s - loss: 0.0832 - mse: 190.9692
45/45 [==============================] - 0s 9ms/step - loss: 0.0831 - mse: 191.6201

45/45 [==============================] - 1s 13ms/step - loss: 0.0831 - mse: 191.6201 - val_loss: 0.5546 - val_mse: 188.1824
Epoch 76/100

 1/45 [..............................] - ETA: 0s - loss: 0.0428 - mse: 181.0905
 7/45 [===>..........................] - ETA: 0s - loss: 0.1124 - mse: 192.1915
13/45 [=======>......................] - ETA: 0s - loss: 0.0990 - mse: 195.4040
19/45 [===========>..................] - ETA: 0s - loss: 0.0871 - mse: 193.3948
25/45 [===============>..............] - ETA: 0s - loss: 0.0805 - mse: 192.7538
31/45 [===================>..........] - ETA: 0s - loss: 0.0762 - mse: 194.4838
37/45 [=======================>......] - ETA: 0s - loss: 0.0727 - mse: 192.1151
43/45 [===========================>..] - ETA: 0s - loss: 0.0702 - mse: 191.7330
45/45 [==============================] - 0s 9ms/step - loss: 0.0693 - mse: 191.6203

45/45 [==============================] - 1s 13ms/step - loss: 0.0693 - mse: 191.6203 - val_loss: 0.4746 - val_mse: 188.1824
Epoch 77/100

 1/45 [..............................] - ETA: 0s - loss: 0.0837 - mse: 207.0365
 7/45 [===>..........................] - ETA: 0s - loss: 0.0615 - mse: 195.0610
13/45 [=======>......................] - ETA: 0s - loss: 0.0546 - mse: 192.1444
19/45 [===========>..................] - ETA: 0s - loss: 0.0497 - mse: 191.2520
25/45 [===============>..............] - ETA: 0s - loss: 0.0467 - mse: 192.6799
31/45 [===================>..........] - ETA: 0s - loss: 0.0466 - mse: 193.1874
37/45 [=======================>......] - ETA: 0s - loss: 0.0471 - mse: 192.6596
43/45 [===========================>..] - ETA: 0s - loss: 0.0460 - mse: 191.4354
45/45 [==============================] - 0s 9ms/step - loss: 0.0459 - mse: 191.6203

45/45 [==============================] - 1s 13ms/step - loss: 0.0459 - mse: 191.6203 - val_loss: 0.4373 - val_mse: 188.1825
Epoch 78/100

 1/45 [..............................] - ETA: 0s - loss: 0.0598 - mse: 212.1144
 7/45 [===>..........................] - ETA: 0s - loss: 0.0517 - mse: 193.1796
12/45 [=======>......................] - ETA: 0s - loss: 0.0474 - mse: 188.2124
18/45 [===========>..................] - ETA: 0s - loss: 0.0447 - mse: 191.3419
24/45 [===============>..............] - ETA: 0s - loss: 0.0437 - mse: 190.1247
30/45 [===================>..........] - ETA: 0s - loss: 0.0415 - mse: 192.1565
36/45 [=======================>......] - ETA: 0s - loss: 0.0416 - mse: 191.6967
42/45 [===========================>..] - ETA: 0s - loss: 0.0408 - mse: 192.0603
45/45 [==============================] - 0s 10ms/step - loss: 0.0404 - mse: 191.6203

45/45 [==============================] - 1s 13ms/step - loss: 0.0404 - mse: 191.6203 - val_loss: 0.5413 - val_mse: 188.1824
Epoch 79/100

 1/45 [..............................] - ETA: 0s - loss: 0.0396 - mse: 186.6371
 7/45 [===>..........................] - ETA: 0s - loss: 0.0753 - mse: 192.5187
13/45 [=======>......................] - ETA: 0s - loss: 0.0785 - mse: 195.8412
19/45 [===========>..................] - ETA: 0s - loss: 0.0796 - mse: 196.3799
25/45 [===============>..............] - ETA: 0s - loss: 0.0916 - mse: 194.2861
31/45 [===================>..........] - ETA: 0s - loss: 0.0875 - mse: 192.1046
37/45 [=======================>......] - ETA: 0s - loss: 0.0867 - mse: 191.6048
43/45 [===========================>..] - ETA: 0s - loss: 0.0841 - mse: 191.5568
45/45 [==============================] - 0s 9ms/step - loss: 0.0830 - mse: 191.6202

45/45 [==============================] - 1s 13ms/step - loss: 0.0830 - mse: 191.6202 - val_loss: 0.4146 - val_mse: 188.1824
Epoch 80/100

 1/45 [..............................] - ETA: 0s - loss: 0.0587 - mse: 197.6217
 6/45 [===>..........................] - ETA: 0s - loss: 0.0613 - mse: 197.5420
12/45 [=======>......................] - ETA: 0s - loss: 0.0732 - mse: 194.5988
18/45 [===========>..................] - ETA: 0s - loss: 0.0757 - mse: 193.2786
24/45 [===============>..............] - ETA: 0s - loss: 0.0779 - mse: 192.0451
30/45 [===================>..........] - ETA: 0s - loss: 0.0813 - mse: 193.2378
36/45 [=======================>......] - ETA: 0s - loss: 0.0795 - mse: 193.3845
42/45 [===========================>..] - ETA: 0s - loss: 0.0759 - mse: 192.1928
45/45 [==============================] - 0s 9ms/step - loss: 0.0751 - mse: 191.6202

45/45 [==============================] - 1s 13ms/step - loss: 0.0751 - mse: 191.6202 - val_loss: 0.4642 - val_mse: 188.1824
Epoch 81/100

 1/45 [..............................] - ETA: 0s - loss: 0.0450 - mse: 181.0235
 7/45 [===>..........................] - ETA: 0s - loss: 0.0580 - mse: 193.3066
13/45 [=======>......................] - ETA: 0s - loss: 0.0516 - mse: 192.3876
19/45 [===========>..................] - ETA: 0s - loss: 0.0491 - mse: 192.9206
25/45 [===============>..............] - ETA: 0s - loss: 0.0465 - mse: 192.1009
31/45 [===================>..........] - ETA: 0s - loss: 0.0448 - mse: 191.2251
37/45 [=======================>......] - ETA: 0s - loss: 0.0435 - mse: 190.6328
43/45 [===========================>..] - ETA: 0s - loss: 0.0442 - mse: 191.2995
45/45 [==============================] - 0s 9ms/step - loss: 0.0443 - mse: 191.6203

45/45 [==============================] - 1s 13ms/step - loss: 0.0443 - mse: 191.6203 - val_loss: 0.4141 - val_mse: 188.1824
Epoch 82/100

 1/45 [..............................] - ETA: 0s - loss: 0.0274 - mse: 194.3664
 7/45 [===>..........................] - ETA: 0s - loss: 0.0341 - mse: 188.4060
13/45 [=======>......................] - ETA: 0s - loss: 0.0328 - mse: 186.9062
19/45 [===========>..................] - ETA: 0s - loss: 0.0336 - mse: 190.5887
25/45 [===============>..............] - ETA: 0s - loss: 0.0325 - mse: 189.8651
31/45 [===================>..........] - ETA: 0s - loss: 0.0355 - mse: 190.6402
37/45 [=======================>......] - ETA: 0s - loss: 0.0353 - mse: 191.0020
43/45 [===========================>..] - ETA: 0s - loss: 0.0363 - mse: 191.4077
45/45 [==============================] - 0s 9ms/step - loss: 0.0365 - mse: 191.6203

45/45 [==============================] - 1s 13ms/step - loss: 0.0365 - mse: 191.6203 - val_loss: 0.4842 - val_mse: 188.1824
Epoch 83/100

 1/45 [..............................] - ETA: 0s - loss: 0.0371 - mse: 193.9175
 7/45 [===>..........................] - ETA: 0s - loss: 0.0301 - mse: 188.9351
13/45 [=======>......................] - ETA: 0s - loss: 0.0330 - mse: 188.1421
19/45 [===========>..................] - ETA: 0s - loss: 0.0344 - mse: 192.6152
25/45 [===============>..............] - ETA: 0s - loss: 0.0347 - mse: 193.0551
31/45 [===================>..........] - ETA: 0s - loss: 0.0345 - mse: 192.7825
37/45 [=======================>......] - ETA: 0s - loss: 0.0348 - mse: 192.9524
43/45 [===========================>..] - ETA: 0s - loss: 0.0353 - mse: 191.6337
45/45 [==============================] - 0s 9ms/step - loss: 0.0352 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0352 - mse: 191.6204 - val_loss: 0.4726 - val_mse: 188.1824
Epoch 84/100

 1/45 [..............................] - ETA: 0s - loss: 0.0338 - mse: 196.3820
 7/45 [===>..........................] - ETA: 0s - loss: 0.0365 - mse: 198.5956
13/45 [=======>......................] - ETA: 0s - loss: 0.0397 - mse: 196.5413
19/45 [===========>..................] - ETA: 0s - loss: 0.0401 - mse: 193.2063
25/45 [===============>..............] - ETA: 0s - loss: 0.0393 - mse: 192.3143
31/45 [===================>..........] - ETA: 0s - loss: 0.0383 - mse: 191.2488
37/45 [=======================>......] - ETA: 0s - loss: 0.0390 - mse: 191.0330
43/45 [===========================>..] - ETA: 0s - loss: 0.0388 - mse: 191.7912
45/45 [==============================] - 0s 9ms/step - loss: 0.0389 - mse: 191.6203

45/45 [==============================] - 1s 13ms/step - loss: 0.0389 - mse: 191.6203 - val_loss: 0.5855 - val_mse: 188.1825
Epoch 85/100

 1/45 [..............................] - ETA: 0s - loss: 0.0490 - mse: 194.1673
 7/45 [===>..........................] - ETA: 0s - loss: 0.0397 - mse: 196.1094
13/45 [=======>......................] - ETA: 0s - loss: 0.0366 - mse: 191.6727
19/45 [===========>..................] - ETA: 0s - loss: 0.0348 - mse: 190.1166
25/45 [===============>..............] - ETA: 0s - loss: 0.0342 - mse: 189.6603
31/45 [===================>..........] - ETA: 0s - loss: 0.0333 - mse: 189.3965
37/45 [=======================>......] - ETA: 0s - loss: 0.0332 - mse: 189.4755
43/45 [===========================>..] - ETA: 0s - loss: 0.0344 - mse: 191.5965
45/45 [==============================] - 0s 9ms/step - loss: 0.0344 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0344 - mse: 191.6204 - val_loss: 0.4999 - val_mse: 188.1825
Epoch 86/100

 1/45 [..............................] - ETA: 0s - loss: 0.0514 - mse: 191.0657
 7/45 [===>..........................] - ETA: 0s - loss: 0.0395 - mse: 197.8013
13/45 [=======>......................] - ETA: 0s - loss: 0.0329 - mse: 193.5153
19/45 [===========>..................] - ETA: 0s - loss: 0.0301 - mse: 192.7455
25/45 [===============>..............] - ETA: 0s - loss: 0.0293 - mse: 191.1494
31/45 [===================>..........] - ETA: 0s - loss: 0.0291 - mse: 190.8629
37/45 [=======================>......] - ETA: 0s - loss: 0.0292 - mse: 190.4196
43/45 [===========================>..] - ETA: 0s - loss: 0.0290 - mse: 191.4845
45/45 [==============================] - 0s 9ms/step - loss: 0.0291 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0291 - mse: 191.6204 - val_loss: 0.4200 - val_mse: 188.1825
Epoch 87/100

 1/45 [..............................] - ETA: 0s - loss: 0.0483 - mse: 212.2237
 7/45 [===>..........................] - ETA: 0s - loss: 0.0340 - mse: 186.2368
13/45 [=======>......................] - ETA: 0s - loss: 0.0318 - mse: 192.1473
19/45 [===========>..................] - ETA: 0s - loss: 0.0294 - mse: 192.2360
25/45 [===============>..............] - ETA: 0s - loss: 0.0299 - mse: 193.3920
31/45 [===================>..........] - ETA: 0s - loss: 0.0303 - mse: 192.4519
37/45 [=======================>......] - ETA: 0s - loss: 0.0308 - mse: 192.0536
43/45 [===========================>..] - ETA: 0s - loss: 0.0312 - mse: 192.0972
45/45 [==============================] - 0s 9ms/step - loss: 0.0310 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0310 - mse: 191.6204 - val_loss: 0.4886 - val_mse: 188.1825
Epoch 88/100

 1/45 [..............................] - ETA: 0s - loss: 0.0268 - mse: 205.1840
 7/45 [===>..........................] - ETA: 0s - loss: 0.0274 - mse: 198.9917
13/45 [=======>......................] - ETA: 0s - loss: 0.0283 - mse: 198.2608
19/45 [===========>..................] - ETA: 0s - loss: 0.0269 - mse: 194.8930
25/45 [===============>..............] - ETA: 0s - loss: 0.0275 - mse: 194.0283
31/45 [===================>..........] - ETA: 0s - loss: 0.0276 - mse: 193.4504
37/45 [=======================>......] - ETA: 0s - loss: 0.0271 - mse: 190.7480
43/45 [===========================>..] - ETA: 0s - loss: 0.0273 - mse: 191.2530
45/45 [==============================] - 0s 9ms/step - loss: 0.0275 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0275 - mse: 191.6204 - val_loss: 0.4269 - val_mse: 188.1825
Epoch 89/100

 1/45 [..............................] - ETA: 0s - loss: 0.0170 - mse: 188.3957
 7/45 [===>..........................] - ETA: 0s - loss: 0.0251 - mse: 192.9631
13/45 [=======>......................] - ETA: 0s - loss: 0.0247 - mse: 191.3932
19/45 [===========>..................] - ETA: 0s - loss: 0.0234 - mse: 189.3883
25/45 [===============>..............] - ETA: 0s - loss: 0.0240 - mse: 189.5408
31/45 [===================>..........] - ETA: 0s - loss: 0.0253 - mse: 191.9552
37/45 [=======================>......] - ETA: 0s - loss: 0.0253 - mse: 192.1960
43/45 [===========================>..] - ETA: 0s - loss: 0.0256 - mse: 191.4493
45/45 [==============================] - 0s 9ms/step - loss: 0.0257 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0257 - mse: 191.6204 - val_loss: 0.3918 - val_mse: 188.1826
Epoch 90/100

 1/45 [..............................] - ETA: 0s - loss: 0.0611 - mse: 186.7423
 7/45 [===>..........................] - ETA: 0s - loss: 0.0432 - mse: 191.8537
13/45 [=======>......................] - ETA: 0s - loss: 0.0415 - mse: 191.1470
19/45 [===========>..................] - ETA: 0s - loss: 0.0424 - mse: 191.2427
25/45 [===============>..............] - ETA: 0s - loss: 0.0407 - mse: 189.6843
31/45 [===================>..........] - ETA: 0s - loss: 0.0405 - mse: 190.5349
37/45 [=======================>......] - ETA: 0s - loss: 0.0406 - mse: 190.8765
43/45 [===========================>..] - ETA: 0s - loss: 0.0412 - mse: 191.8143
45/45 [==============================] - 0s 9ms/step - loss: 0.0407 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0407 - mse: 191.6204 - val_loss: 0.3792 - val_mse: 188.1824
Epoch 91/100

 1/45 [..............................] - ETA: 0s - loss: 0.0452 - mse: 166.9861
 7/45 [===>..........................] - ETA: 0s - loss: 0.0441 - mse: 193.1096
13/45 [=======>......................] - ETA: 0s - loss: 0.0383 - mse: 193.5586
19/45 [===========>..................] - ETA: 0s - loss: 0.0372 - mse: 193.8726
25/45 [===============>..............] - ETA: 0s - loss: 0.0361 - mse: 193.3208
31/45 [===================>..........] - ETA: 0s - loss: 0.0351 - mse: 191.5847
37/45 [=======================>......] - ETA: 0s - loss: 0.0350 - mse: 191.0447
43/45 [===========================>..] - ETA: 0s - loss: 0.0345 - mse: 190.9168
45/45 [==============================] - 0s 9ms/step - loss: 0.0351 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0351 - mse: 191.6204 - val_loss: 0.6035 - val_mse: 188.1826
Epoch 92/100

 1/45 [..............................] - ETA: 0s - loss: 0.0327 - mse: 204.6376
 7/45 [===>..........................] - ETA: 0s - loss: 0.1190 - mse: 196.2909
13/45 [=======>......................] - ETA: 0s - loss: 0.0825 - mse: 190.7561
19/45 [===========>..................] - ETA: 0s - loss: 0.0709 - mse: 191.0080
25/45 [===============>..............] - ETA: 0s - loss: 0.0648 - mse: 190.9542
31/45 [===================>..........] - ETA: 0s - loss: 0.0623 - mse: 191.7450
37/45 [=======================>......] - ETA: 0s - loss: 0.0618 - mse: 191.3295
43/45 [===========================>..] - ETA: 0s - loss: 0.0587 - mse: 191.3922
45/45 [==============================] - 0s 9ms/step - loss: 0.0580 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0580 - mse: 191.6204 - val_loss: 0.4751 - val_mse: 188.1826
Epoch 93/100

 1/45 [..............................] - ETA: 0s - loss: 0.0214 - mse: 211.3158
 7/45 [===>..........................] - ETA: 0s - loss: 0.0402 - mse: 193.5588
13/45 [=======>......................] - ETA: 0s - loss: 0.0363 - mse: 191.4641
19/45 [===========>..................] - ETA: 0s - loss: 0.0345 - mse: 192.2336
25/45 [===============>..............] - ETA: 0s - loss: 0.0322 - mse: 191.4559
31/45 [===================>..........] - ETA: 0s - loss: 0.0307 - mse: 192.0472
37/45 [=======================>......] - ETA: 0s - loss: 0.0309 - mse: 191.6419
43/45 [===========================>..] - ETA: 0s - loss: 0.0321 - mse: 191.7872
45/45 [==============================] - 0s 9ms/step - loss: 0.0320 - mse: 191.6205

45/45 [==============================] - 1s 13ms/step - loss: 0.0320 - mse: 191.6205 - val_loss: 0.5088 - val_mse: 188.1825
Epoch 94/100

 1/45 [..............................] - ETA: 0s - loss: 0.0296 - mse: 200.0861
 7/45 [===>..........................] - ETA: 0s - loss: 0.0221 - mse: 197.9462
13/45 [=======>......................] - ETA: 0s - loss: 0.0206 - mse: 196.9620
19/45 [===========>..................] - ETA: 0s - loss: 0.0209 - mse: 194.5446
25/45 [===============>..............] - ETA: 0s - loss: 0.0212 - mse: 192.4368
31/45 [===================>..........] - ETA: 0s - loss: 0.0219 - mse: 192.2808
37/45 [=======================>......] - ETA: 0s - loss: 0.0222 - mse: 191.7111
43/45 [===========================>..] - ETA: 0s - loss: 0.0229 - mse: 191.4006
45/45 [==============================] - 0s 9ms/step - loss: 0.0231 - mse: 191.6205

45/45 [==============================] - 1s 13ms/step - loss: 0.0231 - mse: 191.6205 - val_loss: 0.4726 - val_mse: 188.1826
Epoch 95/100

 1/45 [..............................] - ETA: 0s - loss: 0.0203 - mse: 180.4014
 7/45 [===>..........................] - ETA: 0s - loss: 0.0233 - mse: 188.4466
13/45 [=======>......................] - ETA: 0s - loss: 0.0237 - mse: 189.5901
19/45 [===========>..................] - ETA: 0s - loss: 0.0241 - mse: 191.1116
25/45 [===============>..............] - ETA: 0s - loss: 0.0236 - mse: 190.1669
31/45 [===================>..........] - ETA: 0s - loss: 0.0270 - mse: 189.2937
37/45 [=======================>......] - ETA: 0s - loss: 0.0293 - mse: 190.7234
43/45 [===========================>..] - ETA: 0s - loss: 0.0318 - mse: 191.7874
45/45 [==============================] - 0s 9ms/step - loss: 0.0317 - mse: 191.6205

45/45 [==============================] - 1s 13ms/step - loss: 0.0317 - mse: 191.6205 - val_loss: 0.5034 - val_mse: 188.1826
Epoch 96/100

 1/45 [..............................] - ETA: 0s - loss: 0.0481 - mse: 202.5768
 7/45 [===>..........................] - ETA: 0s - loss: 0.0484 - mse: 194.5537
13/45 [=======>......................] - ETA: 0s - loss: 0.0436 - mse: 191.1025
19/45 [===========>..................] - ETA: 0s - loss: 0.0429 - mse: 190.9538
25/45 [===============>..............] - ETA: 0s - loss: 0.0404 - mse: 190.8548
31/45 [===================>..........] - ETA: 0s - loss: 0.0394 - mse: 191.3769
37/45 [=======================>......] - ETA: 0s - loss: 0.0376 - mse: 191.6960
43/45 [===========================>..] - ETA: 0s - loss: 0.0363 - mse: 190.9800
45/45 [==============================] - 0s 9ms/step - loss: 0.0360 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0360 - mse: 191.6204 - val_loss: 0.5408 - val_mse: 188.1825
Epoch 97/100

 1/45 [..............................] - ETA: 0s - loss: 0.0129 - mse: 180.0954
 7/45 [===>..........................] - ETA: 0s - loss: 0.0204 - mse: 185.3755
13/45 [=======>......................] - ETA: 0s - loss: 0.0260 - mse: 186.3184
19/45 [===========>..................] - ETA: 0s - loss: 0.0322 - mse: 188.1067
25/45 [===============>..............] - ETA: 0s - loss: 0.0312 - mse: 189.3289
31/45 [===================>..........] - ETA: 0s - loss: 0.0359 - mse: 189.7046
37/45 [=======================>......] - ETA: 0s - loss: 0.0374 - mse: 190.9582
43/45 [===========================>..] - ETA: 0s - loss: 0.0370 - mse: 191.4327
45/45 [==============================] - 0s 9ms/step - loss: 0.0370 - mse: 191.6205

45/45 [==============================] - 1s 13ms/step - loss: 0.0370 - mse: 191.6205 - val_loss: 0.4702 - val_mse: 188.1826
Epoch 98/100

 1/45 [..............................] - ETA: 0s - loss: 0.0311 - mse: 195.5606
 7/45 [===>..........................] - ETA: 0s - loss: 0.0445 - mse: 192.4830
13/45 [=======>......................] - ETA: 0s - loss: 0.0430 - mse: 192.4842
19/45 [===========>..................] - ETA: 0s - loss: 0.0401 - mse: 192.5733
25/45 [===============>..............] - ETA: 0s - loss: 0.0455 - mse: 193.6554
31/45 [===================>..........] - ETA: 0s - loss: 0.0443 - mse: 193.4537
37/45 [=======================>......] - ETA: 0s - loss: 0.0442 - mse: 193.3977
43/45 [===========================>..] - ETA: 0s - loss: 0.0440 - mse: 191.3893
45/45 [==============================] - 0s 9ms/step - loss: 0.0435 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0435 - mse: 191.6204 - val_loss: 0.7013 - val_mse: 188.1826
Epoch 99/100

 1/45 [..............................] - ETA: 0s - loss: 0.0373 - mse: 188.8732
 7/45 [===>..........................] - ETA: 0s - loss: 0.0439 - mse: 191.8010
13/45 [=======>......................] - ETA: 0s - loss: 0.0385 - mse: 191.3167
19/45 [===========>..................] - ETA: 0s - loss: 0.0376 - mse: 192.7923
25/45 [===============>..............] - ETA: 0s - loss: 0.0393 - mse: 191.8737
31/45 [===================>..........] - ETA: 0s - loss: 0.0420 - mse: 193.6894
37/45 [=======================>......] - ETA: 0s - loss: 0.0411 - mse: 193.1578
43/45 [===========================>..] - ETA: 0s - loss: 0.0387 - mse: 192.1918
45/45 [==============================] - 0s 9ms/step - loss: 0.0381 - mse: 191.6204

45/45 [==============================] - 1s 13ms/step - loss: 0.0381 - mse: 191.6204 - val_loss: 0.6544 - val_mse: 188.1826
Epoch 100/100

 1/45 [..............................] - ETA: 0s - loss: 0.0556 - mse: 196.0611
 7/45 [===>..........................] - ETA: 0s - loss: 0.0898 - mse: 191.5802
13/45 [=======>......................] - ETA: 0s - loss: 0.0812 - mse: 192.0348
19/45 [===========>..................] - ETA: 0s - loss: 0.0781 - mse: 189.5999
25/45 [===============>..............] - ETA: 0s - loss: 0.0812 - mse: 192.0569
31/45 [===================>..........] - ETA: 0s - loss: 0.0875 - mse: 192.3333
37/45 [=======================>......] - ETA: 0s - loss: 0.1019 - mse: 191.6632
43/45 [===========================>..] - ETA: 0s - loss: 0.1264 - mse: 191.6645
45/45 [==============================] - 0s 9ms/step - loss: 0.1287 - mse: 191.6203

45/45 [==============================] - 1s 13ms/step - loss: 0.1287 - mse: 191.6203 - val_loss: 1.1864 - val_mse: 188.1825

Run completed: runs/2023-04-03T22-32-55Z

Training run 7/9 (flags = list(128, 0.001, 200, 100, "tanh")) 
Using run directory runs/2023-04-03T22-33-54Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 106) %>%
+   layer_dense(units = FLAGS$nodes, activation .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('mse')
+  .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   second_bikes_matrix, second_bikes_train_set$count, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(a .... [TRUNCATED] 
Epoch 1/100

 1/45 [..............................] - ETA: 14s - loss: 5.0074 - mse: 186.7254
16/45 [=========>....................] - ETA: 0s - loss: 4.0038 - mse: 195.2439 
31/45 [===================>..........] - ETA: 0s - loss: 3.5521 - mse: 193.2101
42/45 [===========================>..] - ETA: 0s - loss: 3.3450 - mse: 192.2758
45/45 [==============================] - 0s 4ms/step - loss: 3.3091 - mse: 191.6117

45/45 [==============================] - 1s 19ms/step - loss: 3.3091 - mse: 191.6117 - val_loss: 2.6417 - val_mse: 188.1749
Epoch 2/100

 1/45 [..............................] - ETA: 0s - loss: 2.5633 - mse: 193.1960
16/45 [=========>....................] - ETA: 0s - loss: 2.5163 - mse: 192.8637
30/45 [===================>..........] - ETA: 0s - loss: 2.4353 - mse: 192.2354
45/45 [==============================] - 0s 3ms/step - loss: 2.3643 - mse: 191.6122

45/45 [==============================] - 0s 7ms/step - loss: 2.3643 - mse: 191.6122 - val_loss: 2.1949 - val_mse: 188.1753
Epoch 3/100

 1/45 [..............................] - ETA: 0s - loss: 2.1883 - mse: 199.7166
15/45 [=========>....................] - ETA: 0s - loss: 2.0910 - mse: 190.3643
30/45 [===================>..........] - ETA: 0s - loss: 2.0529 - mse: 193.7270
45/45 [==============================] - 0s 3ms/step - loss: 2.0020 - mse: 191.6126

45/45 [==============================] - 0s 7ms/step - loss: 2.0020 - mse: 191.6126 - val_loss: 1.9108 - val_mse: 188.1755
Epoch 4/100

 1/45 [..............................] - ETA: 0s - loss: 1.8523 - mse: 187.1201
16/45 [=========>....................] - ETA: 0s - loss: 1.8320 - mse: 196.5628
31/45 [===================>..........] - ETA: 0s - loss: 1.7916 - mse: 193.7049
45/45 [==============================] - 0s 3ms/step - loss: 1.7543 - mse: 191.6128

45/45 [==============================] - 0s 7ms/step - loss: 1.7543 - mse: 191.6128 - val_loss: 1.6980 - val_mse: 188.1758
Epoch 5/100

 1/45 [..............................] - ETA: 0s - loss: 1.6277 - mse: 181.2836
15/45 [=========>....................] - ETA: 0s - loss: 1.6338 - mse: 196.6162
30/45 [===================>..........] - ETA: 0s - loss: 1.5898 - mse: 192.8504
44/45 [============================>.] - ETA: 0s - loss: 1.5606 - mse: 191.6223
45/45 [==============================] - 0s 4ms/step - loss: 1.5603 - mse: 191.6131

45/45 [==============================] - 0s 7ms/step - loss: 1.5603 - mse: 191.6131 - val_loss: 1.5091 - val_mse: 188.1761
Epoch 6/100

 1/45 [..............................] - ETA: 0s - loss: 1.4518 - mse: 193.1709
15/45 [=========>....................] - ETA: 0s - loss: 1.4489 - mse: 190.5269
30/45 [===================>..........] - ETA: 0s - loss: 1.4256 - mse: 192.4373
44/45 [============================>.] - ETA: 0s - loss: 1.4012 - mse: 191.4231
45/45 [==============================] - 0s 4ms/step - loss: 1.4017 - mse: 191.6134

45/45 [==============================] - 0s 7ms/step - loss: 1.4017 - mse: 191.6134 - val_loss: 1.3559 - val_mse: 188.1763
Epoch 7/100

 1/45 [..............................] - ETA: 0s - loss: 1.3084 - mse: 188.6913
16/45 [=========>....................] - ETA: 0s - loss: 1.3005 - mse: 189.9286
31/45 [===================>..........] - ETA: 0s - loss: 1.2799 - mse: 191.8128
45/45 [==============================] - 0s 3ms/step - loss: 1.2630 - mse: 191.6137

45/45 [==============================] - 0s 7ms/step - loss: 1.2630 - mse: 191.6137 - val_loss: 1.2224 - val_mse: 188.1767
Epoch 8/100

 1/45 [..............................] - ETA: 0s - loss: 1.2243 - mse: 197.5638
15/45 [=========>....................] - ETA: 0s - loss: 1.1689 - mse: 187.0833
29/45 [==================>...........] - ETA: 0s - loss: 1.1700 - mse: 192.9767
43/45 [===========================>..] - ETA: 0s - loss: 1.1490 - mse: 192.1816
45/45 [==============================] - 0s 4ms/step - loss: 1.1458 - mse: 191.6140

45/45 [==============================] - 0s 7ms/step - loss: 1.1458 - mse: 191.6140 - val_loss: 1.1033 - val_mse: 188.1769
Epoch 9/100

 1/45 [..............................] - ETA: 0s - loss: 1.0127 - mse: 168.1700
15/45 [=========>....................] - ETA: 0s - loss: 1.0585 - mse: 187.3002
29/45 [==================>...........] - ETA: 0s - loss: 1.0532 - mse: 190.3178
43/45 [===========================>..] - ETA: 0s - loss: 1.0428 - mse: 191.0644
45/45 [==============================] - 0s 4ms/step - loss: 1.0431 - mse: 191.6142

45/45 [==============================] - 0s 7ms/step - loss: 1.0431 - mse: 191.6142 - val_loss: 1.0142 - val_mse: 188.1772
Epoch 10/100

 1/45 [..............................] - ETA: 0s - loss: 0.9466 - mse: 171.2433
15/45 [=========>....................] - ETA: 0s - loss: 0.9785 - mse: 190.2005
29/45 [==================>...........] - ETA: 0s - loss: 0.9641 - mse: 190.1458
44/45 [============================>.] - ETA: 0s - loss: 0.9536 - mse: 191.5769
45/45 [==============================] - 0s 4ms/step - loss: 0.9536 - mse: 191.6145

45/45 [==============================] - 0s 7ms/step - loss: 0.9536 - mse: 191.6145 - val_loss: 0.9445 - val_mse: 188.1775
Epoch 11/100

 1/45 [..............................] - ETA: 0s - loss: 0.8753 - mse: 182.7909
16/45 [=========>....................] - ETA: 0s - loss: 0.9081 - mse: 194.0924
31/45 [===================>..........] - ETA: 0s - loss: 0.8858 - mse: 190.7061
45/45 [==============================] - 0s 3ms/step - loss: 0.8790 - mse: 191.6148

45/45 [==============================] - 0s 7ms/step - loss: 0.8790 - mse: 191.6148 - val_loss: 0.8876 - val_mse: 188.1777
Epoch 12/100

 1/45 [..............................] - ETA: 0s - loss: 0.9368 - mse: 223.0606
14/45 [========>.....................] - ETA: 0s - loss: 0.8427 - mse: 196.3321
28/45 [=================>............] - ETA: 0s - loss: 0.8246 - mse: 192.2087
43/45 [===========================>..] - ETA: 0s - loss: 0.8118 - mse: 191.4815
45/45 [==============================] - 0s 4ms/step - loss: 0.8114 - mse: 191.6151

45/45 [==============================] - 0s 7ms/step - loss: 0.8114 - mse: 191.6151 - val_loss: 0.8057 - val_mse: 188.1780
Epoch 13/100

 1/45 [..............................] - ETA: 0s - loss: 0.7997 - mse: 191.4211
15/45 [=========>....................] - ETA: 0s - loss: 0.7820 - mse: 191.3024
29/45 [==================>...........] - ETA: 0s - loss: 0.7720 - mse: 193.1080
43/45 [===========================>..] - ETA: 0s - loss: 0.7587 - mse: 191.3480
45/45 [==============================] - 0s 4ms/step - loss: 0.7581 - mse: 191.6153

45/45 [==============================] - 0s 7ms/step - loss: 0.7581 - mse: 191.6153 - val_loss: 0.7522 - val_mse: 188.1782
Epoch 14/100

 1/45 [..............................] - ETA: 0s - loss: 0.7417 - mse: 206.4025
15/45 [=========>....................] - ETA: 0s - loss: 0.7365 - mse: 195.6951
30/45 [===================>..........] - ETA: 0s - loss: 0.7159 - mse: 192.5603
45/45 [==============================] - 0s 4ms/step - loss: 0.7067 - mse: 191.6155

45/45 [==============================] - 0s 7ms/step - loss: 0.7067 - mse: 191.6155 - val_loss: 0.7147 - val_mse: 188.1784
Epoch 15/100

 1/45 [..............................] - ETA: 0s - loss: 0.6650 - mse: 188.3527
15/45 [=========>....................] - ETA: 0s - loss: 0.6695 - mse: 189.4492
29/45 [==================>...........] - ETA: 0s - loss: 0.6719 - mse: 191.4936
43/45 [===========================>..] - ETA: 0s - loss: 0.6630 - mse: 191.5979
45/45 [==============================] - 0s 4ms/step - loss: 0.6619 - mse: 191.6158

45/45 [==============================] - 0s 7ms/step - loss: 0.6619 - mse: 191.6158 - val_loss: 0.6656 - val_mse: 188.1786
Epoch 16/100

 1/45 [..............................] - ETA: 0s - loss: 0.6622 - mse: 195.2641
16/45 [=========>....................] - ETA: 0s - loss: 0.6233 - mse: 187.8042
31/45 [===================>..........] - ETA: 0s - loss: 0.6254 - mse: 190.8594
45/45 [==============================] - 0s 3ms/step - loss: 0.6207 - mse: 191.6160

45/45 [==============================] - 0s 7ms/step - loss: 0.6207 - mse: 191.6160 - val_loss: 0.6207 - val_mse: 188.1788
Epoch 17/100

 1/45 [..............................] - ETA: 0s - loss: 0.6020 - mse: 189.0175
15/45 [=========>....................] - ETA: 0s - loss: 0.6005 - mse: 192.5027
30/45 [===================>..........] - ETA: 0s - loss: 0.5847 - mse: 189.5272
44/45 [============================>.] - ETA: 0s - loss: 0.5858 - mse: 191.6528
45/45 [==============================] - 0s 3ms/step - loss: 0.5855 - mse: 191.6162

45/45 [==============================] - 0s 7ms/step - loss: 0.5855 - mse: 191.6162 - val_loss: 0.5982 - val_mse: 188.1790
Epoch 18/100

 1/45 [..............................] - ETA: 0s - loss: 0.5950 - mse: 200.5619
15/45 [=========>....................] - ETA: 0s - loss: 0.5654 - mse: 194.1831
29/45 [==================>...........] - ETA: 0s - loss: 0.5589 - mse: 192.0804
43/45 [===========================>..] - ETA: 0s - loss: 0.5528 - mse: 191.4283
45/45 [==============================] - 0s 4ms/step - loss: 0.5526 - mse: 191.6163

45/45 [==============================] - 0s 7ms/step - loss: 0.5526 - mse: 191.6163 - val_loss: 0.5611 - val_mse: 188.1792
Epoch 19/100

 1/45 [..............................] - ETA: 0s - loss: 0.5633 - mse: 196.3215
16/45 [=========>....................] - ETA: 0s - loss: 0.5339 - mse: 191.9266
30/45 [===================>..........] - ETA: 0s - loss: 0.5272 - mse: 191.8939
45/45 [==============================] - 0s 4ms/step - loss: 0.5239 - mse: 191.6165

45/45 [==============================] - 0s 7ms/step - loss: 0.5239 - mse: 191.6165 - val_loss: 0.5686 - val_mse: 188.1794
Epoch 20/100

 1/45 [..............................] - ETA: 0s - loss: 0.5137 - mse: 198.6866
15/45 [=========>....................] - ETA: 0s - loss: 0.5164 - mse: 193.0873
30/45 [===================>..........] - ETA: 0s - loss: 0.5033 - mse: 192.4395
44/45 [============================>.] - ETA: 0s - loss: 0.4953 - mse: 191.6440
45/45 [==============================] - 0s 4ms/step - loss: 0.4954 - mse: 191.6167

45/45 [==============================] - 0s 7ms/step - loss: 0.4954 - mse: 191.6167 - val_loss: 0.5245 - val_mse: 188.1795
Epoch 21/100

 1/45 [..............................] - ETA: 0s - loss: 0.4635 - mse: 187.5749
15/45 [=========>....................] - ETA: 0s - loss: 0.4916 - mse: 192.1503
29/45 [==================>...........] - ETA: 0s - loss: 0.4892 - mse: 194.2484
43/45 [===========================>..] - ETA: 0s - loss: 0.4755 - mse: 191.4813
45/45 [==============================] - 0s 4ms/step - loss: 0.4753 - mse: 191.6169

45/45 [==============================] - 0s 7ms/step - loss: 0.4753 - mse: 191.6169 - val_loss: 0.5219 - val_mse: 188.1797
Epoch 22/100

 1/45 [..............................] - ETA: 0s - loss: 0.4852 - mse: 196.1736
15/45 [=========>....................] - ETA: 0s - loss: 0.4461 - mse: 187.5329
29/45 [==================>...........] - ETA: 0s - loss: 0.4478 - mse: 190.1918
44/45 [============================>.] - ETA: 0s - loss: 0.4499 - mse: 191.5325
45/45 [==============================] - 0s 4ms/step - loss: 0.4500 - mse: 191.6171

45/45 [==============================] - 0s 7ms/step - loss: 0.4500 - mse: 191.6171 - val_loss: 0.4763 - val_mse: 188.1798
Epoch 23/100

 1/45 [..............................] - ETA: 0s - loss: 0.4561 - mse: 200.2336
16/45 [=========>....................] - ETA: 0s - loss: 0.4252 - mse: 189.2858
31/45 [===================>..........] - ETA: 0s - loss: 0.4309 - mse: 190.7201
45/45 [==============================] - 0s 3ms/step - loss: 0.4317 - mse: 191.6171

45/45 [==============================] - 0s 7ms/step - loss: 0.4317 - mse: 191.6171 - val_loss: 0.4478 - val_mse: 188.1799
Epoch 24/100

 1/45 [..............................] - ETA: 0s - loss: 0.4243 - mse: 196.5752
15/45 [=========>....................] - ETA: 0s - loss: 0.4129 - mse: 191.7249
29/45 [==================>...........] - ETA: 0s - loss: 0.4078 - mse: 191.6050
43/45 [===========================>..] - ETA: 0s - loss: 0.4069 - mse: 191.3767
45/45 [==============================] - 0s 4ms/step - loss: 0.4078 - mse: 191.6173

45/45 [==============================] - 0s 7ms/step - loss: 0.4078 - mse: 191.6173 - val_loss: 0.4435 - val_mse: 188.1801
Epoch 25/100

 1/45 [..............................] - ETA: 0s - loss: 0.4078 - mse: 192.8548
16/45 [=========>....................] - ETA: 0s - loss: 0.4109 - mse: 193.3677
31/45 [===================>..........] - ETA: 0s - loss: 0.4006 - mse: 192.6772
45/45 [==============================] - 0s 3ms/step - loss: 0.3949 - mse: 191.6174

45/45 [==============================] - 0s 7ms/step - loss: 0.3949 - mse: 191.6174 - val_loss: 0.4185 - val_mse: 188.1802
Epoch 26/100

 1/45 [..............................] - ETA: 0s - loss: 0.3796 - mse: 187.0621
15/45 [=========>....................] - ETA: 0s - loss: 0.3737 - mse: 187.8459
29/45 [==================>...........] - ETA: 0s - loss: 0.3689 - mse: 189.0498
44/45 [============================>.] - ETA: 0s - loss: 0.3728 - mse: 191.6144
45/45 [==============================] - 0s 4ms/step - loss: 0.3728 - mse: 191.6176

45/45 [==============================] - 0s 7ms/step - loss: 0.3728 - mse: 191.6176 - val_loss: 0.3936 - val_mse: 188.1803
Epoch 27/100

 1/45 [..............................] - ETA: 0s - loss: 0.3867 - mse: 194.0688
16/45 [=========>....................] - ETA: 0s - loss: 0.3789 - mse: 189.9392
31/45 [===================>..........] - ETA: 0s - loss: 0.3750 - mse: 190.7072
45/45 [==============================] - 0s 3ms/step - loss: 0.3706 - mse: 191.6177

45/45 [==============================] - 0s 7ms/step - loss: 0.3706 - mse: 191.6177 - val_loss: 0.4212 - val_mse: 188.1804
Epoch 28/100

 1/45 [..............................] - ETA: 0s - loss: 0.3356 - mse: 178.7764
15/45 [=========>....................] - ETA: 0s - loss: 0.3492 - mse: 192.5238
29/45 [==================>...........] - ETA: 0s - loss: 0.3452 - mse: 192.3088
43/45 [===========================>..] - ETA: 0s - loss: 0.3455 - mse: 191.3955
45/45 [==============================] - 0s 4ms/step - loss: 0.3467 - mse: 191.6178

45/45 [==============================] - 0s 7ms/step - loss: 0.3467 - mse: 191.6178 - val_loss: 0.4346 - val_mse: 188.1805
Epoch 29/100

 1/45 [..............................] - ETA: 0s - loss: 0.2919 - mse: 181.3882
15/45 [=========>....................] - ETA: 0s - loss: 0.3507 - mse: 193.3520
30/45 [===================>..........] - ETA: 0s - loss: 0.3401 - mse: 191.8008
41/45 [==========================>...] - ETA: 0s - loss: 0.3354 - mse: 190.7144
45/45 [==============================] - 0s 4ms/step - loss: 0.3358 - mse: 191.6179

45/45 [==============================] - 0s 7ms/step - loss: 0.3358 - mse: 191.6179 - val_loss: 0.4066 - val_mse: 188.1806
Epoch 30/100

 1/45 [..............................] - ETA: 0s - loss: 0.3205 - mse: 189.6443
16/45 [=========>....................] - ETA: 0s - loss: 0.3198 - mse: 189.2100
30/45 [===================>..........] - ETA: 0s - loss: 0.3241 - mse: 190.9914
44/45 [============================>.] - ETA: 0s - loss: 0.3240 - mse: 191.6133
45/45 [==============================] - 0s 4ms/step - loss: 0.3239 - mse: 191.6180

45/45 [==============================] - 0s 7ms/step - loss: 0.3239 - mse: 191.6180 - val_loss: 0.4138 - val_mse: 188.1807
Epoch 31/100

 1/45 [..............................] - ETA: 0s - loss: 0.3219 - mse: 186.3763
15/45 [=========>....................] - ETA: 0s - loss: 0.3171 - mse: 189.6461
29/45 [==================>...........] - ETA: 0s - loss: 0.3155 - mse: 191.4929
43/45 [===========================>..] - ETA: 0s - loss: 0.3132 - mse: 191.4217
45/45 [==============================] - 0s 4ms/step - loss: 0.3127 - mse: 191.6181

45/45 [==============================] - 0s 7ms/step - loss: 0.3127 - mse: 191.6181 - val_loss: 0.3700 - val_mse: 188.1808
Epoch 32/100

 1/45 [..............................] - ETA: 0s - loss: 0.3134 - mse: 192.3367
15/45 [=========>....................] - ETA: 0s - loss: 0.3056 - mse: 189.2180
30/45 [===================>..........] - ETA: 0s - loss: 0.3019 - mse: 191.1429
44/45 [============================>.] - ETA: 0s - loss: 0.3031 - mse: 191.6274
45/45 [==============================] - 0s 4ms/step - loss: 0.3031 - mse: 191.6181

45/45 [==============================] - 0s 7ms/step - loss: 0.3031 - mse: 191.6181 - val_loss: 0.3854 - val_mse: 188.1808
Epoch 33/100

 1/45 [..............................] - ETA: 0s - loss: 0.2807 - mse: 191.7699
15/45 [=========>....................] - ETA: 0s - loss: 0.2977 - mse: 191.8886
29/45 [==================>...........] - ETA: 0s - loss: 0.2926 - mse: 192.0332
43/45 [===========================>..] - ETA: 0s - loss: 0.2921 - mse: 191.4460
45/45 [==============================] - 0s 4ms/step - loss: 0.2927 - mse: 191.6183

45/45 [==============================] - 0s 7ms/step - loss: 0.2927 - mse: 191.6183 - val_loss: 0.3839 - val_mse: 188.1810
Epoch 34/100

 1/45 [..............................] - ETA: 0s - loss: 0.2959 - mse: 195.9211
15/45 [=========>....................] - ETA: 0s - loss: 0.2951 - mse: 195.6675
29/45 [==================>...........] - ETA: 0s - loss: 0.2867 - mse: 192.3855
43/45 [===========================>..] - ETA: 0s - loss: 0.2851 - mse: 191.5159
45/45 [==============================] - 0s 4ms/step - loss: 0.2845 - mse: 191.6183

45/45 [==============================] - 0s 7ms/step - loss: 0.2845 - mse: 191.6183 - val_loss: 0.3571 - val_mse: 188.1810
Epoch 35/100

 1/45 [..............................] - ETA: 0s - loss: 0.2438 - mse: 193.9469
15/45 [=========>....................] - ETA: 0s - loss: 0.2762 - mse: 191.8861
29/45 [==================>...........] - ETA: 0s - loss: 0.2781 - mse: 193.5103
43/45 [===========================>..] - ETA: 0s - loss: 0.2737 - mse: 191.5170
45/45 [==============================] - 0s 4ms/step - loss: 0.2737 - mse: 191.6184

45/45 [==============================] - 0s 7ms/step - loss: 0.2737 - mse: 191.6184 - val_loss: 0.3600 - val_mse: 188.1810
Epoch 36/100

 1/45 [..............................] - ETA: 0s - loss: 0.2561 - mse: 202.9383
15/45 [=========>....................] - ETA: 0s - loss: 0.2816 - mse: 193.8396
30/45 [===================>..........] - ETA: 0s - loss: 0.2790 - mse: 194.0162
44/45 [============================>.] - ETA: 0s - loss: 0.2702 - mse: 191.5045
45/45 [==============================] - 0s 4ms/step - loss: 0.2707 - mse: 191.6184

45/45 [==============================] - 0s 7ms/step - loss: 0.2707 - mse: 191.6184 - val_loss: 0.3413 - val_mse: 188.1811
Epoch 37/100

 1/45 [..............................] - ETA: 0s - loss: 0.2432 - mse: 186.5045
15/45 [=========>....................] - ETA: 0s - loss: 0.2548 - mse: 187.9133
29/45 [==================>...........] - ETA: 0s - loss: 0.2554 - mse: 190.1571
44/45 [============================>.] - ETA: 0s - loss: 0.2554 - mse: 191.6112
45/45 [==============================] - 0s 4ms/step - loss: 0.2555 - mse: 191.6185

45/45 [==============================] - 0s 7ms/step - loss: 0.2555 - mse: 191.6185 - val_loss: 0.3170 - val_mse: 188.1812
Epoch 38/100

 1/45 [..............................] - ETA: 0s - loss: 0.2392 - mse: 195.4005
15/45 [=========>....................] - ETA: 0s - loss: 0.2717 - mse: 197.2868
29/45 [==================>...........] - ETA: 0s - loss: 0.2588 - mse: 192.4302
43/45 [===========================>..] - ETA: 0s - loss: 0.2569 - mse: 191.8159
45/45 [==============================] - 0s 4ms/step - loss: 0.2562 - mse: 191.6185

45/45 [==============================] - 0s 7ms/step - loss: 0.2562 - mse: 191.6185 - val_loss: 0.3282 - val_mse: 188.1812
Epoch 39/100

 1/45 [..............................] - ETA: 0s - loss: 0.2702 - mse: 203.3468
15/45 [=========>....................] - ETA: 0s - loss: 0.2481 - mse: 197.1517
29/45 [==================>...........] - ETA: 0s - loss: 0.2443 - mse: 193.8419
43/45 [===========================>..] - ETA: 0s - loss: 0.2425 - mse: 191.5135
45/45 [==============================] - 0s 4ms/step - loss: 0.2430 - mse: 191.6186

45/45 [==============================] - 0s 7ms/step - loss: 0.2430 - mse: 191.6186 - val_loss: 0.3487 - val_mse: 188.1813
Epoch 40/100

 1/45 [..............................] - ETA: 0s - loss: 0.2123 - mse: 185.1556
15/45 [=========>....................] - ETA: 0s - loss: 0.2411 - mse: 194.4034
29/45 [==================>...........] - ETA: 0s - loss: 0.2414 - mse: 193.3098
43/45 [===========================>..] - ETA: 0s - loss: 0.2367 - mse: 191.3434
45/45 [==============================] - 0s 4ms/step - loss: 0.2366 - mse: 191.6187

45/45 [==============================] - 0s 7ms/step - loss: 0.2366 - mse: 191.6187 - val_loss: 0.3846 - val_mse: 188.1813
Epoch 41/100

 1/45 [..............................] - ETA: 0s - loss: 0.2535 - mse: 190.0364
15/45 [=========>....................] - ETA: 0s - loss: 0.2269 - mse: 187.7323
29/45 [==================>...........] - ETA: 0s - loss: 0.2300 - mse: 189.2454
43/45 [===========================>..] - ETA: 0s - loss: 0.2300 - mse: 191.5496
45/45 [==============================] - 0s 4ms/step - loss: 0.2315 - mse: 191.6188

45/45 [==============================] - 0s 7ms/step - loss: 0.2315 - mse: 191.6188 - val_loss: 0.2845 - val_mse: 188.1814
Epoch 42/100

 1/45 [..............................] - ETA: 0s - loss: 0.1971 - mse: 182.0007
15/45 [=========>....................] - ETA: 0s - loss: 0.2291 - mse: 193.9521
29/45 [==================>...........] - ETA: 0s - loss: 0.2263 - mse: 191.1883
44/45 [============================>.] - ETA: 0s - loss: 0.2244 - mse: 191.5272
45/45 [==============================] - 0s 4ms/step - loss: 0.2244 - mse: 191.6188

45/45 [==============================] - 0s 7ms/step - loss: 0.2244 - mse: 191.6188 - val_loss: 0.2894 - val_mse: 188.1814
Epoch 43/100

 1/45 [..............................] - ETA: 0s - loss: 0.1853 - mse: 174.7989
15/45 [=========>....................] - ETA: 0s - loss: 0.2153 - mse: 188.9487
29/45 [==================>...........] - ETA: 0s - loss: 0.2188 - mse: 191.9902
43/45 [===========================>..] - ETA: 0s - loss: 0.2173 - mse: 192.1032
45/45 [==============================] - 0s 4ms/step - loss: 0.2165 - mse: 191.6189

45/45 [==============================] - 0s 7ms/step - loss: 0.2165 - mse: 191.6189 - val_loss: 0.3176 - val_mse: 188.1815
Epoch 44/100

 1/45 [..............................] - ETA: 0s - loss: 0.2514 - mse: 205.3117
15/45 [=========>....................] - ETA: 0s - loss: 0.2087 - mse: 190.8822
30/45 [===================>..........] - ETA: 0s - loss: 0.2131 - mse: 192.0835
44/45 [============================>.] - ETA: 0s - loss: 0.2123 - mse: 191.7233
45/45 [==============================] - 0s 4ms/step - loss: 0.2122 - mse: 191.6189

45/45 [==============================] - 0s 7ms/step - loss: 0.2122 - mse: 191.6189 - val_loss: 0.3442 - val_mse: 188.1815
Epoch 45/100

 1/45 [..............................] - ETA: 0s - loss: 0.2178 - mse: 200.8480
15/45 [=========>....................] - ETA: 0s - loss: 0.2114 - mse: 189.5681
29/45 [==================>...........] - ETA: 0s - loss: 0.2148 - mse: 192.2727
43/45 [===========================>..] - ETA: 0s - loss: 0.2165 - mse: 191.7554
45/45 [==============================] - 0s 4ms/step - loss: 0.2156 - mse: 191.6189

45/45 [==============================] - 0s 7ms/step - loss: 0.2156 - mse: 191.6189 - val_loss: 0.2836 - val_mse: 188.1816
Epoch 46/100

 1/45 [..............................] - ETA: 0s - loss: 0.2441 - mse: 213.2739
15/45 [=========>....................] - ETA: 0s - loss: 0.2088 - mse: 191.6508
29/45 [==================>...........] - ETA: 0s - loss: 0.2103 - mse: 193.1022
43/45 [===========================>..] - ETA: 0s - loss: 0.2094 - mse: 191.5810
45/45 [==============================] - 0s 4ms/step - loss: 0.2092 - mse: 191.6189

45/45 [==============================] - 0s 7ms/step - loss: 0.2092 - mse: 191.6189 - val_loss: 0.3889 - val_mse: 188.1816
Epoch 47/100

 1/45 [..............................] - ETA: 0s - loss: 0.2487 - mse: 195.8845
15/45 [=========>....................] - ETA: 0s - loss: 0.2210 - mse: 193.2018
29/45 [==================>...........] - ETA: 0s - loss: 0.2089 - mse: 190.3827
43/45 [===========================>..] - ETA: 0s - loss: 0.2066 - mse: 191.6067
45/45 [==============================] - 0s 4ms/step - loss: 0.2067 - mse: 191.6190

45/45 [==============================] - 0s 7ms/step - loss: 0.2067 - mse: 191.6190 - val_loss: 0.2810 - val_mse: 188.1816
Epoch 48/100

 1/45 [..............................] - ETA: 0s - loss: 0.1754 - mse: 171.7614
15/45 [=========>....................] - ETA: 0s - loss: 0.1984 - mse: 195.1614
29/45 [==================>...........] - ETA: 0s - loss: 0.1936 - mse: 192.2126
43/45 [===========================>..] - ETA: 0s - loss: 0.1966 - mse: 191.4441
45/45 [==============================] - 0s 4ms/step - loss: 0.1970 - mse: 191.6191

45/45 [==============================] - 0s 7ms/step - loss: 0.1970 - mse: 191.6191 - val_loss: 0.3347 - val_mse: 188.1817
Epoch 49/100

 1/45 [..............................] - ETA: 0s - loss: 0.2720 - mse: 219.9918
15/45 [=========>....................] - ETA: 0s - loss: 0.1916 - mse: 185.2270
29/45 [==================>...........] - ETA: 0s - loss: 0.1918 - mse: 188.8583
43/45 [===========================>..] - ETA: 0s - loss: 0.1919 - mse: 191.0198
45/45 [==============================] - 0s 4ms/step - loss: 0.1925 - mse: 191.6191

45/45 [==============================] - 0s 7ms/step - loss: 0.1925 - mse: 191.6191 - val_loss: 0.3803 - val_mse: 188.1817
Epoch 50/100

 1/45 [..............................] - ETA: 0s - loss: 0.1773 - mse: 199.0678
15/45 [=========>....................] - ETA: 0s - loss: 0.1986 - mse: 192.0331
29/45 [==================>...........] - ETA: 0s - loss: 0.1939 - mse: 193.0292
43/45 [===========================>..] - ETA: 0s - loss: 0.1917 - mse: 191.5630
45/45 [==============================] - 0s 4ms/step - loss: 0.1914 - mse: 191.6191

45/45 [==============================] - 0s 7ms/step - loss: 0.1914 - mse: 191.6191 - val_loss: 0.3222 - val_mse: 188.1817
Epoch 51/100

 1/45 [..............................] - ETA: 0s - loss: 0.1697 - mse: 194.4627
15/45 [=========>....................] - ETA: 0s - loss: 0.1795 - mse: 187.5946
29/45 [==================>...........] - ETA: 0s - loss: 0.1778 - mse: 190.5511
43/45 [===========================>..] - ETA: 0s - loss: 0.1775 - mse: 191.4939
45/45 [==============================] - 0s 4ms/step - loss: 0.1774 - mse: 191.6191

45/45 [==============================] - 0s 7ms/step - loss: 0.1774 - mse: 191.6191 - val_loss: 0.3399 - val_mse: 188.1818
Epoch 52/100

 1/45 [..............................] - ETA: 0s - loss: 0.1635 - mse: 170.0522
15/45 [=========>....................] - ETA: 0s - loss: 0.1898 - mse: 194.9430
29/45 [==================>...........] - ETA: 0s - loss: 0.1865 - mse: 192.7219
43/45 [===========================>..] - ETA: 0s - loss: 0.1797 - mse: 191.5248
45/45 [==============================] - 0s 4ms/step - loss: 0.1795 - mse: 191.6192

45/45 [==============================] - 0s 7ms/step - loss: 0.1795 - mse: 191.6192 - val_loss: 0.3252 - val_mse: 188.1818
Epoch 53/100

 1/45 [..............................] - ETA: 0s - loss: 0.1655 - mse: 195.1658
15/45 [=========>....................] - ETA: 0s - loss: 0.1784 - mse: 194.6311
29/45 [==================>...........] - ETA: 0s - loss: 0.1698 - mse: 192.7679
43/45 [===========================>..] - ETA: 0s - loss: 0.1706 - mse: 191.9594
45/45 [==============================] - 0s 4ms/step - loss: 0.1703 - mse: 191.6192

45/45 [==============================] - 0s 7ms/step - loss: 0.1703 - mse: 191.6192 - val_loss: 0.2792 - val_mse: 188.1817
Epoch 54/100

 1/45 [..............................] - ETA: 0s - loss: 0.1761 - mse: 192.1404
15/45 [=========>....................] - ETA: 0s - loss: 0.1651 - mse: 196.5302
29/45 [==================>...........] - ETA: 0s - loss: 0.1623 - mse: 192.8764
43/45 [===========================>..] - ETA: 0s - loss: 0.1640 - mse: 191.8691
45/45 [==============================] - 0s 4ms/step - loss: 0.1637 - mse: 191.6192

45/45 [==============================] - 0s 7ms/step - loss: 0.1637 - mse: 191.6192 - val_loss: 0.3915 - val_mse: 188.1817
Epoch 55/100

 1/45 [..............................] - ETA: 0s - loss: 0.1695 - mse: 206.7571
15/45 [=========>....................] - ETA: 0s - loss: 0.1831 - mse: 192.8150
29/45 [==================>...........] - ETA: 0s - loss: 0.1778 - mse: 191.6864
43/45 [===========================>..] - ETA: 0s - loss: 0.1754 - mse: 192.1621
45/45 [==============================] - 0s 4ms/step - loss: 0.1748 - mse: 191.6192

45/45 [==============================] - 0s 7ms/step - loss: 0.1748 - mse: 191.6192 - val_loss: 0.3071 - val_mse: 188.1819
Epoch 56/100

 1/45 [..............................] - ETA: 0s - loss: 0.1544 - mse: 179.4969
14/45 [========>.....................] - ETA: 0s - loss: 0.1585 - mse: 191.6977
25/45 [===============>..............] - ETA: 0s - loss: 0.1557 - mse: 189.6157
38/45 [========================>.....] - ETA: 0s - loss: 0.1578 - mse: 191.1377
45/45 [==============================] - 0s 4ms/step - loss: 0.1610 - mse: 191.6193

45/45 [==============================] - 0s 8ms/step - loss: 0.1610 - mse: 191.6193 - val_loss: 0.2884 - val_mse: 188.1818
Epoch 57/100

 1/45 [..............................] - ETA: 0s - loss: 0.1478 - mse: 195.3103
15/45 [=========>....................] - ETA: 0s - loss: 0.1634 - mse: 192.5241
29/45 [==================>...........] - ETA: 0s - loss: 0.1616 - mse: 192.4750
43/45 [===========================>..] - ETA: 0s - loss: 0.1570 - mse: 191.6669
45/45 [==============================] - 0s 4ms/step - loss: 0.1567 - mse: 191.6193

45/45 [==============================] - 0s 7ms/step - loss: 0.1567 - mse: 191.6193 - val_loss: 0.2944 - val_mse: 188.1820
Epoch 58/100

 1/45 [..............................] - ETA: 0s - loss: 0.1675 - mse: 192.8692
14/45 [========>.....................] - ETA: 0s - loss: 0.1532 - mse: 190.5443
28/45 [=================>............] - ETA: 0s - loss: 0.1525 - mse: 191.0995
42/45 [===========================>..] - ETA: 0s - loss: 0.1498 - mse: 190.7913
45/45 [==============================] - 0s 4ms/step - loss: 0.1512 - mse: 191.6194

45/45 [==============================] - 0s 7ms/step - loss: 0.1512 - mse: 191.6194 - val_loss: 0.2843 - val_mse: 188.1819
Epoch 59/100

 1/45 [..............................] - ETA: 0s - loss: 0.1245 - mse: 180.6368
13/45 [=======>......................] - ETA: 0s - loss: 0.1556 - mse: 192.0653
27/45 [=================>............] - ETA: 0s - loss: 0.1491 - mse: 191.8348
41/45 [==========================>...] - ETA: 0s - loss: 0.1484 - mse: 191.7284
45/45 [==============================] - 0s 4ms/step - loss: 0.1490 - mse: 191.6194

45/45 [==============================] - 0s 7ms/step - loss: 0.1490 - mse: 191.6194 - val_loss: 0.3458 - val_mse: 188.1819
Epoch 60/100

 1/45 [..............................] - ETA: 0s - loss: 0.1436 - mse: 169.7809
15/45 [=========>....................] - ETA: 0s - loss: 0.1547 - mse: 192.1071
29/45 [==================>...........] - ETA: 0s - loss: 0.1595 - mse: 193.2606
43/45 [===========================>..] - ETA: 0s - loss: 0.1629 - mse: 191.3979
45/45 [==============================] - 0s 4ms/step - loss: 0.1633 - mse: 191.6193

45/45 [==============================] - 0s 7ms/step - loss: 0.1633 - mse: 191.6193 - val_loss: 0.2575 - val_mse: 188.1820
Epoch 61/100

 1/45 [..............................] - ETA: 0s - loss: 0.1498 - mse: 192.2187
15/45 [=========>....................] - ETA: 0s - loss: 0.1587 - mse: 195.3565
29/45 [==================>...........] - ETA: 0s - loss: 0.1546 - mse: 194.2608
43/45 [===========================>..] - ETA: 0s - loss: 0.1474 - mse: 191.3025
45/45 [==============================] - 0s 4ms/step - loss: 0.1480 - mse: 191.6195

45/45 [==============================] - 0s 7ms/step - loss: 0.1480 - mse: 191.6195 - val_loss: 0.2661 - val_mse: 188.1820
Epoch 62/100

 1/45 [..............................] - ETA: 0s - loss: 0.1161 - mse: 192.2713
15/45 [=========>....................] - ETA: 0s - loss: 0.1493 - mse: 194.0067
28/45 [=================>............] - ETA: 0s - loss: 0.1411 - mse: 192.1193
42/45 [===========================>..] - ETA: 0s - loss: 0.1405 - mse: 191.8579
45/45 [==============================] - 0s 4ms/step - loss: 0.1406 - mse: 191.6195

45/45 [==============================] - 0s 7ms/step - loss: 0.1406 - mse: 191.6195 - val_loss: 0.2591 - val_mse: 188.1820
Epoch 63/100

 1/45 [..............................] - ETA: 0s - loss: 0.1780 - mse: 202.3988
14/45 [========>.....................] - ETA: 0s - loss: 0.1510 - mse: 194.9357
28/45 [=================>............] - ETA: 0s - loss: 0.1510 - mse: 192.7563
42/45 [===========================>..] - ETA: 0s - loss: 0.1440 - mse: 190.3955
45/45 [==============================] - 0s 4ms/step - loss: 0.1456 - mse: 191.6195

45/45 [==============================] - 0s 7ms/step - loss: 0.1456 - mse: 191.6195 - val_loss: 0.2394 - val_mse: 188.1821
Epoch 64/100

 1/45 [..............................] - ETA: 0s - loss: 0.1340 - mse: 213.6846
14/45 [========>.....................] - ETA: 0s - loss: 0.1334 - mse: 194.3800
28/45 [=================>............] - ETA: 0s - loss: 0.1338 - mse: 191.6117
42/45 [===========================>..] - ETA: 0s - loss: 0.1369 - mse: 191.3018
45/45 [==============================] - 0s 4ms/step - loss: 0.1365 - mse: 191.6195

45/45 [==============================] - 0s 8ms/step - loss: 0.1365 - mse: 191.6195 - val_loss: 0.3426 - val_mse: 188.1821
Epoch 65/100

 1/45 [..............................] - ETA: 0s - loss: 0.0997 - mse: 191.7830
15/45 [=========>....................] - ETA: 0s - loss: 0.1325 - mse: 183.8359
29/45 [==================>...........] - ETA: 0s - loss: 0.1405 - mse: 190.4862
43/45 [===========================>..] - ETA: 0s - loss: 0.1421 - mse: 191.3895
45/45 [==============================] - 0s 4ms/step - loss: 0.1427 - mse: 191.6195

45/45 [==============================] - 0s 7ms/step - loss: 0.1427 - mse: 191.6195 - val_loss: 0.2744 - val_mse: 188.1821
Epoch 66/100

 1/45 [..............................] - ETA: 0s - loss: 0.1241 - mse: 191.9517
15/45 [=========>....................] - ETA: 0s - loss: 0.1289 - mse: 190.5580
30/45 [===================>..........] - ETA: 0s - loss: 0.1282 - mse: 191.8311
44/45 [============================>.] - ETA: 0s - loss: 0.1298 - mse: 191.6038
45/45 [==============================] - 0s 4ms/step - loss: 0.1297 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1297 - mse: 191.6196 - val_loss: 0.2439 - val_mse: 188.1821
Epoch 67/100

 1/45 [..............................] - ETA: 0s - loss: 0.1473 - mse: 199.0868
15/45 [=========>....................] - ETA: 0s - loss: 0.1248 - mse: 192.3537
29/45 [==================>...........] - ETA: 0s - loss: 0.1229 - mse: 190.1066
43/45 [===========================>..] - ETA: 0s - loss: 0.1245 - mse: 191.5626
45/45 [==============================] - 0s 4ms/step - loss: 0.1246 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1246 - mse: 191.6196 - val_loss: 0.2790 - val_mse: 188.1821
Epoch 68/100

 1/45 [..............................] - ETA: 0s - loss: 0.0994 - mse: 196.8868
15/45 [=========>....................] - ETA: 0s - loss: 0.1263 - mse: 194.0855
29/45 [==================>...........] - ETA: 0s - loss: 0.1223 - mse: 192.3414
43/45 [===========================>..] - ETA: 0s - loss: 0.1224 - mse: 191.9337
45/45 [==============================] - 0s 4ms/step - loss: 0.1217 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1217 - mse: 191.6196 - val_loss: 0.3006 - val_mse: 188.1822
Epoch 69/100

 1/45 [..............................] - ETA: 0s - loss: 0.1227 - mse: 198.4763
15/45 [=========>....................] - ETA: 0s - loss: 0.1332 - mse: 190.2332
30/45 [===================>..........] - ETA: 0s - loss: 0.1327 - mse: 190.3194
44/45 [============================>.] - ETA: 0s - loss: 0.1333 - mse: 191.6678
45/45 [==============================] - 0s 4ms/step - loss: 0.1332 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1332 - mse: 191.6196 - val_loss: 0.2951 - val_mse: 188.1822
Epoch 70/100

 1/45 [..............................] - ETA: 0s - loss: 0.1051 - mse: 202.3226
15/45 [=========>....................] - ETA: 0s - loss: 0.1294 - mse: 195.0763
29/45 [==================>...........] - ETA: 0s - loss: 0.1238 - mse: 191.9234
43/45 [===========================>..] - ETA: 0s - loss: 0.1225 - mse: 191.6214
45/45 [==============================] - 0s 4ms/step - loss: 0.1222 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1222 - mse: 191.6196 - val_loss: 0.2642 - val_mse: 188.1822
Epoch 71/100

 1/45 [..............................] - ETA: 0s - loss: 0.1375 - mse: 197.2850
15/45 [=========>....................] - ETA: 0s - loss: 0.1337 - mse: 194.6301
29/45 [==================>...........] - ETA: 0s - loss: 0.1224 - mse: 192.2055
43/45 [===========================>..] - ETA: 0s - loss: 0.1220 - mse: 191.8036
45/45 [==============================] - 0s 4ms/step - loss: 0.1218 - mse: 191.6197

45/45 [==============================] - 0s 7ms/step - loss: 0.1218 - mse: 191.6197 - val_loss: 0.2549 - val_mse: 188.1822
Epoch 72/100

 1/45 [..............................] - ETA: 0s - loss: 0.1171 - mse: 177.8798
15/45 [=========>....................] - ETA: 0s - loss: 0.1231 - mse: 193.1358
29/45 [==================>...........] - ETA: 0s - loss: 0.1260 - mse: 193.6316
43/45 [===========================>..] - ETA: 0s - loss: 0.1190 - mse: 191.4500
45/45 [==============================] - 0s 4ms/step - loss: 0.1190 - mse: 191.6197

45/45 [==============================] - 0s 7ms/step - loss: 0.1190 - mse: 191.6197 - val_loss: 0.2587 - val_mse: 188.1822
Epoch 73/100

 1/45 [..............................] - ETA: 0s - loss: 0.1005 - mse: 189.9180
15/45 [=========>....................] - ETA: 0s - loss: 0.1106 - mse: 190.7351
29/45 [==================>...........] - ETA: 0s - loss: 0.1119 - mse: 190.9650
43/45 [===========================>..] - ETA: 0s - loss: 0.1124 - mse: 191.2953
45/45 [==============================] - 0s 4ms/step - loss: 0.1129 - mse: 191.6197

45/45 [==============================] - 0s 7ms/step - loss: 0.1129 - mse: 191.6197 - val_loss: 0.3024 - val_mse: 188.1822
Epoch 74/100

 1/45 [..............................] - ETA: 0s - loss: 0.1004 - mse: 191.7945
15/45 [=========>....................] - ETA: 0s - loss: 0.1256 - mse: 193.6250
29/45 [==================>...........] - ETA: 0s - loss: 0.1224 - mse: 193.6567
43/45 [===========================>..] - ETA: 0s - loss: 0.1168 - mse: 192.0140
45/45 [==============================] - 0s 4ms/step - loss: 0.1163 - mse: 191.6197

45/45 [==============================] - 0s 7ms/step - loss: 0.1163 - mse: 191.6197 - val_loss: 0.2570 - val_mse: 188.1822
Epoch 75/100

 1/45 [..............................] - ETA: 0s - loss: 0.1004 - mse: 180.3363
15/45 [=========>....................] - ETA: 0s - loss: 0.1125 - mse: 191.7445
25/45 [===============>..............] - ETA: 0s - loss: 0.1104 - mse: 190.8392
39/45 [=========================>....] - ETA: 0s - loss: 0.1074 - mse: 191.3038
45/45 [==============================] - 0s 4ms/step - loss: 0.1073 - mse: 191.6197

45/45 [==============================] - 0s 8ms/step - loss: 0.1073 - mse: 191.6197 - val_loss: 0.3067 - val_mse: 188.1823
Epoch 76/100

 1/45 [..............................] - ETA: 0s - loss: 0.0943 - mse: 172.3976
15/45 [=========>....................] - ETA: 0s - loss: 0.1126 - mse: 192.1508
29/45 [==================>...........] - ETA: 0s - loss: 0.1126 - mse: 193.8186
44/45 [============================>.] - ETA: 0s - loss: 0.1114 - mse: 191.5512
45/45 [==============================] - 0s 4ms/step - loss: 0.1115 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1115 - mse: 191.6198 - val_loss: 0.2263 - val_mse: 188.1823
Epoch 77/100

 1/45 [..............................] - ETA: 0s - loss: 0.0850 - mse: 187.7823
15/45 [=========>....................] - ETA: 0s - loss: 0.1072 - mse: 192.3375
29/45 [==================>...........] - ETA: 0s - loss: 0.1086 - mse: 192.4191
43/45 [===========================>..] - ETA: 0s - loss: 0.1076 - mse: 191.6976
45/45 [==============================] - 0s 4ms/step - loss: 0.1077 - mse: 191.6197

45/45 [==============================] - 0s 7ms/step - loss: 0.1077 - mse: 191.6197 - val_loss: 0.2404 - val_mse: 188.1823
Epoch 78/100

 1/45 [..............................] - ETA: 0s - loss: 0.0935 - mse: 184.9405
15/45 [=========>....................] - ETA: 0s - loss: 0.1026 - mse: 192.6470
29/45 [==================>...........] - ETA: 0s - loss: 0.1063 - mse: 193.7595
43/45 [===========================>..] - ETA: 0s - loss: 0.1028 - mse: 190.9966
45/45 [==============================] - 0s 4ms/step - loss: 0.1040 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1040 - mse: 191.6198 - val_loss: 0.2873 - val_mse: 188.1823
Epoch 79/100

 1/45 [..............................] - ETA: 0s - loss: 0.1054 - mse: 177.0444
15/45 [=========>....................] - ETA: 0s - loss: 0.1186 - mse: 188.2922
30/45 [===================>..........] - ETA: 0s - loss: 0.1139 - mse: 191.2905
45/45 [==============================] - 0s 4ms/step - loss: 0.1114 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1114 - mse: 191.6198 - val_loss: 0.2629 - val_mse: 188.1823
Epoch 80/100

 1/45 [..............................] - ETA: 0s - loss: 0.0670 - mse: 175.4559
16/45 [=========>....................] - ETA: 0s - loss: 0.1090 - mse: 192.8732
30/45 [===================>..........] - ETA: 0s - loss: 0.1050 - mse: 192.2784
45/45 [==============================] - 0s 4ms/step - loss: 0.1047 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1047 - mse: 191.6198 - val_loss: 0.3562 - val_mse: 188.1823
Epoch 81/100

 1/45 [..............................] - ETA: 0s - loss: 0.0749 - mse: 180.6021
15/45 [=========>....................] - ETA: 0s - loss: 0.0942 - mse: 188.3411
29/45 [==================>...........] - ETA: 0s - loss: 0.0986 - mse: 189.4955
43/45 [===========================>..] - ETA: 0s - loss: 0.1011 - mse: 191.8607
45/45 [==============================] - 0s 4ms/step - loss: 0.1004 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1004 - mse: 191.6198 - val_loss: 0.3235 - val_mse: 188.1823
Epoch 82/100

 1/45 [..............................] - ETA: 0s - loss: 0.1025 - mse: 191.8915
15/45 [=========>....................] - ETA: 0s - loss: 0.0924 - mse: 186.9114
29/45 [==================>...........] - ETA: 0s - loss: 0.0956 - mse: 190.7461
43/45 [===========================>..] - ETA: 0s - loss: 0.0971 - mse: 191.7401
45/45 [==============================] - 0s 4ms/step - loss: 0.0975 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0975 - mse: 191.6199 - val_loss: 0.4225 - val_mse: 188.1824
Epoch 83/100

 1/45 [..............................] - ETA: 0s - loss: 0.1410 - mse: 186.5149
16/45 [=========>....................] - ETA: 0s - loss: 0.1233 - mse: 193.9366
30/45 [===================>..........] - ETA: 0s - loss: 0.1143 - mse: 191.9491
44/45 [============================>.] - ETA: 0s - loss: 0.1072 - mse: 191.5955
45/45 [==============================] - 0s 4ms/step - loss: 0.1072 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1072 - mse: 191.6198 - val_loss: 0.2337 - val_mse: 188.1824
Epoch 84/100

 1/45 [..............................] - ETA: 0s - loss: 0.1109 - mse: 210.2137
15/45 [=========>....................] - ETA: 0s - loss: 0.1024 - mse: 188.8736
29/45 [==================>...........] - ETA: 0s - loss: 0.1042 - mse: 191.0227
43/45 [===========================>..] - ETA: 0s - loss: 0.1012 - mse: 191.3219
45/45 [==============================] - 0s 4ms/step - loss: 0.1019 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.1019 - mse: 191.6199 - val_loss: 0.2377 - val_mse: 188.1824
Epoch 85/100

 1/45 [..............................] - ETA: 0s - loss: 0.1009 - mse: 180.8519
15/45 [=========>....................] - ETA: 0s - loss: 0.1051 - mse: 190.9364
29/45 [==================>...........] - ETA: 0s - loss: 0.1040 - mse: 192.3854
43/45 [===========================>..] - ETA: 0s - loss: 0.1029 - mse: 191.7259
45/45 [==============================] - 0s 4ms/step - loss: 0.1028 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1028 - mse: 191.6198 - val_loss: 0.2645 - val_mse: 188.1824
Epoch 86/100

 1/45 [..............................] - ETA: 0s - loss: 0.0620 - mse: 193.3279
15/45 [=========>....................] - ETA: 0s - loss: 0.0904 - mse: 190.3324
29/45 [==================>...........] - ETA: 0s - loss: 0.0921 - mse: 191.8501
43/45 [===========================>..] - ETA: 0s - loss: 0.0910 - mse: 191.9097
45/45 [==============================] - 0s 4ms/step - loss: 0.0907 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0907 - mse: 191.6199 - val_loss: 0.2900 - val_mse: 188.1824
Epoch 87/100

 1/45 [..............................] - ETA: 0s - loss: 0.0890 - mse: 181.6203
15/45 [=========>....................] - ETA: 0s - loss: 0.1081 - mse: 191.5805
29/45 [==================>...........] - ETA: 0s - loss: 0.1077 - mse: 192.4980
43/45 [===========================>..] - ETA: 0s - loss: 0.1043 - mse: 191.7675
45/45 [==============================] - 0s 4ms/step - loss: 0.1034 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.1034 - mse: 191.6199 - val_loss: 0.2776 - val_mse: 188.1824
Epoch 88/100

 1/45 [..............................] - ETA: 0s - loss: 0.0740 - mse: 212.1377
15/45 [=========>....................] - ETA: 0s - loss: 0.1021 - mse: 192.3293
29/45 [==================>...........] - ETA: 0s - loss: 0.0937 - mse: 190.8469
43/45 [===========================>..] - ETA: 0s - loss: 0.0948 - mse: 191.8617
45/45 [==============================] - 0s 4ms/step - loss: 0.0942 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0942 - mse: 191.6199 - val_loss: 0.2655 - val_mse: 188.1824
Epoch 89/100

 1/45 [..............................] - ETA: 0s - loss: 0.0942 - mse: 202.7926
15/45 [=========>....................] - ETA: 0s - loss: 0.0854 - mse: 191.0935
29/45 [==================>...........] - ETA: 0s - loss: 0.0852 - mse: 191.6417
43/45 [===========================>..] - ETA: 0s - loss: 0.0840 - mse: 191.4986
45/45 [==============================] - 0s 4ms/step - loss: 0.0843 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0843 - mse: 191.6200 - val_loss: 0.2599 - val_mse: 188.1824
Epoch 90/100

 1/45 [..............................] - ETA: 0s - loss: 0.1173 - mse: 204.2573
14/45 [========>.....................] - ETA: 0s - loss: 0.0870 - mse: 191.6074
28/45 [=================>............] - ETA: 0s - loss: 0.0865 - mse: 190.3992
42/45 [===========================>..] - ETA: 0s - loss: 0.0848 - mse: 191.5257
45/45 [==============================] - 0s 4ms/step - loss: 0.0846 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0846 - mse: 191.6199 - val_loss: 0.3222 - val_mse: 188.1824
Epoch 91/100

 1/45 [..............................] - ETA: 0s - loss: 0.0777 - mse: 188.2633
15/45 [=========>....................] - ETA: 0s - loss: 0.0827 - mse: 193.3316
29/45 [==================>...........] - ETA: 0s - loss: 0.0804 - mse: 191.5424
43/45 [===========================>..] - ETA: 0s - loss: 0.0825 - mse: 191.6084
45/45 [==============================] - 0s 4ms/step - loss: 0.0831 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0831 - mse: 191.6200 - val_loss: 0.2446 - val_mse: 188.1824
Epoch 92/100

 1/45 [..............................] - ETA: 0s - loss: 0.0606 - mse: 178.8800
15/45 [=========>....................] - ETA: 0s - loss: 0.0866 - mse: 191.2458
29/45 [==================>...........] - ETA: 0s - loss: 0.0867 - mse: 191.4632
43/45 [===========================>..] - ETA: 0s - loss: 0.0850 - mse: 192.0035
45/45 [==============================] - 0s 4ms/step - loss: 0.0844 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0844 - mse: 191.6199 - val_loss: 0.2925 - val_mse: 188.1824
Epoch 93/100

 1/45 [..............................] - ETA: 0s - loss: 0.0483 - mse: 173.2784
15/45 [=========>....................] - ETA: 0s - loss: 0.0777 - mse: 188.6212
29/45 [==================>...........] - ETA: 0s - loss: 0.0774 - mse: 191.2377
43/45 [===========================>..] - ETA: 0s - loss: 0.0807 - mse: 191.8001
45/45 [==============================] - 0s 4ms/step - loss: 0.0804 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0804 - mse: 191.6200 - val_loss: 0.2505 - val_mse: 188.1825
Epoch 94/100

 1/45 [..............................] - ETA: 0s - loss: 0.0754 - mse: 180.3901
15/45 [=========>....................] - ETA: 0s - loss: 0.0707 - mse: 187.2637
29/45 [==================>...........] - ETA: 0s - loss: 0.0729 - mse: 192.1942
43/45 [===========================>..] - ETA: 0s - loss: 0.0761 - mse: 192.3757
45/45 [==============================] - 0s 4ms/step - loss: 0.0756 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0756 - mse: 191.6200 - val_loss: 0.2752 - val_mse: 188.1825
Epoch 95/100

 1/45 [..............................] - ETA: 0s - loss: 0.0645 - mse: 212.4359
15/45 [=========>....................] - ETA: 0s - loss: 0.0805 - mse: 191.4216
29/45 [==================>...........] - ETA: 0s - loss: 0.0822 - mse: 191.9423
43/45 [===========================>..] - ETA: 0s - loss: 0.0808 - mse: 191.6159
45/45 [==============================] - 0s 4ms/step - loss: 0.0806 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0806 - mse: 191.6200 - val_loss: 0.2649 - val_mse: 188.1825
Epoch 96/100

 1/45 [..............................] - ETA: 0s - loss: 0.0585 - mse: 173.4699
15/45 [=========>....................] - ETA: 0s - loss: 0.0827 - mse: 187.8714
29/45 [==================>...........] - ETA: 0s - loss: 0.0785 - mse: 189.5326
43/45 [===========================>..] - ETA: 0s - loss: 0.0786 - mse: 191.6460
45/45 [==============================] - 0s 4ms/step - loss: 0.0783 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0783 - mse: 191.6200 - val_loss: 0.2615 - val_mse: 188.1825
Epoch 97/100

 1/45 [..............................] - ETA: 0s - loss: 0.0715 - mse: 174.8864
15/45 [=========>....................] - ETA: 0s - loss: 0.0729 - mse: 194.6330
29/45 [==================>...........] - ETA: 0s - loss: 0.0767 - mse: 192.4384
43/45 [===========================>..] - ETA: 0s - loss: 0.0738 - mse: 191.5031
45/45 [==============================] - 0s 4ms/step - loss: 0.0736 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0736 - mse: 191.6200 - val_loss: 0.3384 - val_mse: 188.1825
Epoch 98/100

 1/45 [..............................] - ETA: 0s - loss: 0.0579 - mse: 171.3763
15/45 [=========>....................] - ETA: 0s - loss: 0.0730 - mse: 189.6598
29/45 [==================>...........] - ETA: 0s - loss: 0.0745 - mse: 190.2441
43/45 [===========================>..] - ETA: 0s - loss: 0.0770 - mse: 191.3936
45/45 [==============================] - 0s 4ms/step - loss: 0.0770 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0770 - mse: 191.6200 - val_loss: 0.3518 - val_mse: 188.1825
Epoch 99/100

 1/45 [..............................] - ETA: 0s - loss: 0.0586 - mse: 180.8239
15/45 [=========>....................] - ETA: 0s - loss: 0.0795 - mse: 192.2417
29/45 [==================>...........] - ETA: 0s - loss: 0.0734 - mse: 189.8736
43/45 [===========================>..] - ETA: 0s - loss: 0.0735 - mse: 191.4135
45/45 [==============================] - 0s 4ms/step - loss: 0.0733 - mse: 191.6201

45/45 [==============================] - 0s 7ms/step - loss: 0.0733 - mse: 191.6201 - val_loss: 0.2693 - val_mse: 188.1825
Epoch 100/100

 1/45 [..............................] - ETA: 0s - loss: 0.0846 - mse: 182.3291
15/45 [=========>....................] - ETA: 0s - loss: 0.0750 - mse: 191.4472
27/45 [=================>............] - ETA: 0s - loss: 0.0757 - mse: 192.8487
40/45 [=========================>....] - ETA: 0s - loss: 0.0741 - mse: 192.3981
45/45 [==============================] - 0s 4ms/step - loss: 0.0729 - mse: 191.6201

45/45 [==============================] - 0s 7ms/step - loss: 0.0729 - mse: 191.6201 - val_loss: 0.2722 - val_mse: 188.1825

Run completed: runs/2023-04-03T22-33-54Z

Training run 8/9 (flags = list(64, 0.05, 500, 100, "tanh")) 
Using run directory runs/2023-04-03T22-34-27Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 106) %>%
+   layer_dense(units = FLAGS$nodes, activation .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('mse')
+  .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   second_bikes_matrix, second_bikes_train_set$count, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(a .... [TRUNCATED] 
Epoch 1/100

 1/18 [>.............................] - ETA: 5s - loss: 4.6541 - mse: 179.3517
16/18 [=========================>....] - ETA: 0s - loss: 4.2088 - mse: 191.1838
18/18 [==============================] - 0s 3ms/step - loss: 4.1636 - mse: 191.6115

18/18 [==============================] - 1s 42ms/step - loss: 4.1636 - mse: 191.6115 - val_loss: 3.6824 - val_mse: 188.1743
Epoch 2/100

 1/18 [>.............................] - ETA: 0s - loss: 3.7083 - mse: 193.2915
15/18 [========================>.....] - ETA: 0s - loss: 3.4480 - mse: 192.3131
18/18 [==============================] - 0s 4ms/step - loss: 3.4115 - mse: 191.6116

18/18 [==============================] - 0s 13ms/step - loss: 3.4115 - mse: 191.6116 - val_loss: 3.1808 - val_mse: 188.1745
Epoch 3/100

 1/18 [>.............................] - ETA: 0s - loss: 3.1801 - mse: 197.8851
16/18 [=========================>....] - ETA: 0s - loss: 3.0530 - mse: 192.6900
18/18 [==============================] - 0s 3ms/step - loss: 3.0350 - mse: 191.6117

18/18 [==============================] - 0s 12ms/step - loss: 3.0350 - mse: 191.6117 - val_loss: 2.8917 - val_mse: 188.1746
Epoch 4/100

 1/18 [>.............................] - ETA: 0s - loss: 2.9026 - mse: 200.0071
16/18 [=========================>....] - ETA: 0s - loss: 2.7811 - mse: 191.7915
18/18 [==============================] - 0s 3ms/step - loss: 2.7696 - mse: 191.6118

18/18 [==============================] - 0s 12ms/step - loss: 2.7696 - mse: 191.6118 - val_loss: 2.6639 - val_mse: 188.1747
Epoch 5/100

 1/18 [>.............................] - ETA: 0s - loss: 2.6299 - mse: 186.6298
15/18 [========================>.....] - ETA: 0s - loss: 2.5683 - mse: 191.3020
18/18 [==============================] - 0s 4ms/step - loss: 2.5546 - mse: 191.6120

18/18 [==============================] - 0s 13ms/step - loss: 2.5546 - mse: 191.6120 - val_loss: 2.4830 - val_mse: 188.1749
Epoch 6/100

 1/18 [>.............................] - ETA: 0s - loss: 2.4695 - mse: 195.3553
16/18 [=========================>....] - ETA: 0s - loss: 2.3906 - mse: 190.9411
18/18 [==============================] - 0s 3ms/step - loss: 2.3852 - mse: 191.6121

18/18 [==============================] - 0s 12ms/step - loss: 2.3852 - mse: 191.6121 - val_loss: 2.3414 - val_mse: 188.1750
Epoch 7/100

 1/18 [>.............................] - ETA: 0s - loss: 2.2674 - mse: 177.9457
15/18 [========================>.....] - ETA: 0s - loss: 2.2502 - mse: 190.5717
18/18 [==============================] - 0s 4ms/step - loss: 2.2459 - mse: 191.6122

18/18 [==============================] - 0s 13ms/step - loss: 2.2459 - mse: 191.6122 - val_loss: 2.2148 - val_mse: 188.1751
Epoch 8/100

 1/18 [>.............................] - ETA: 0s - loss: 2.1876 - mse: 197.1911
16/18 [=========================>....] - ETA: 0s - loss: 2.1299 - mse: 191.7428
18/18 [==============================] - 0s 3ms/step - loss: 2.1242 - mse: 191.6123

18/18 [==============================] - 0s 12ms/step - loss: 2.1242 - mse: 191.6123 - val_loss: 2.1031 - val_mse: 188.1752
Epoch 9/100

 1/18 [>.............................] - ETA: 0s - loss: 2.0226 - mse: 187.5493
16/18 [=========================>....] - ETA: 0s - loss: 2.0156 - mse: 190.0666
18/18 [==============================] - 0s 3ms/step - loss: 2.0159 - mse: 191.6124

18/18 [==============================] - 0s 12ms/step - loss: 2.0159 - mse: 191.6124 - val_loss: 2.0078 - val_mse: 188.1753
Epoch 10/100

 1/18 [>.............................] - ETA: 0s - loss: 1.9759 - mse: 199.4091
15/18 [========================>.....] - ETA: 0s - loss: 1.9257 - mse: 191.7837
18/18 [==============================] - 0s 4ms/step - loss: 1.9210 - mse: 191.6125

18/18 [==============================] - 0s 13ms/step - loss: 1.9210 - mse: 191.6125 - val_loss: 1.9095 - val_mse: 188.1754
Epoch 11/100

 1/18 [>.............................] - ETA: 0s - loss: 1.8936 - mse: 194.3424
13/18 [====================>.........] - ETA: 0s - loss: 1.8492 - mse: 192.4784
18/18 [==============================] - 0s 4ms/step - loss: 1.8367 - mse: 191.6126

18/18 [==============================] - 0s 14ms/step - loss: 1.8367 - mse: 191.6126 - val_loss: 1.8261 - val_mse: 188.1755
Epoch 12/100

 1/18 [>.............................] - ETA: 0s - loss: 1.7807 - mse: 183.7129
15/18 [========================>.....] - ETA: 0s - loss: 1.7659 - mse: 191.2888
18/18 [==============================] - 0s 4ms/step - loss: 1.7606 - mse: 191.6127

18/18 [==============================] - 0s 13ms/step - loss: 1.7606 - mse: 191.6127 - val_loss: 1.7490 - val_mse: 188.1756
Epoch 13/100

 1/18 [>.............................] - ETA: 0s - loss: 1.7045 - mse: 185.0901
16/18 [=========================>....] - ETA: 0s - loss: 1.6942 - mse: 191.2194
18/18 [==============================] - 0s 3ms/step - loss: 1.6921 - mse: 191.6128

18/18 [==============================] - 0s 12ms/step - loss: 1.6921 - mse: 191.6128 - val_loss: 1.6778 - val_mse: 188.1757
Epoch 14/100

 1/18 [>.............................] - ETA: 0s - loss: 1.6544 - mse: 193.6754
16/18 [=========================>....] - ETA: 0s - loss: 1.6297 - mse: 190.9487
18/18 [==============================] - 0s 3ms/step - loss: 1.6287 - mse: 191.6129

18/18 [==============================] - 0s 14ms/step - loss: 1.6287 - mse: 191.6129 - val_loss: 1.6157 - val_mse: 188.1758
Epoch 15/100

 1/18 [>.............................] - ETA: 0s - loss: 1.5695 - mse: 185.9149
15/18 [========================>.....] - ETA: 0s - loss: 1.5760 - mse: 192.3752
18/18 [==============================] - 0s 3ms/step - loss: 1.5699 - mse: 191.6130

18/18 [==============================] - 0s 12ms/step - loss: 1.5699 - mse: 191.6130 - val_loss: 1.5530 - val_mse: 188.1758
Epoch 16/100

 1/18 [>.............................] - ETA: 0s - loss: 1.5735 - mse: 196.9424
15/18 [========================>.....] - ETA: 0s - loss: 1.5173 - mse: 191.6922
18/18 [==============================] - 0s 4ms/step - loss: 1.5139 - mse: 191.6131

18/18 [==============================] - 0s 13ms/step - loss: 1.5139 - mse: 191.6131 - val_loss: 1.4997 - val_mse: 188.1759
Epoch 17/100

 1/18 [>.............................] - ETA: 0s - loss: 1.4903 - mse: 193.7807
16/18 [=========================>....] - ETA: 0s - loss: 1.4638 - mse: 191.6462
18/18 [==============================] - 0s 3ms/step - loss: 1.4622 - mse: 191.6132

18/18 [==============================] - 0s 13ms/step - loss: 1.4622 - mse: 191.6132 - val_loss: 1.4507 - val_mse: 188.1760
Epoch 18/100

 1/18 [>.............................] - ETA: 0s - loss: 1.4107 - mse: 185.9304
16/18 [=========================>....] - ETA: 0s - loss: 1.4162 - mse: 192.2591
18/18 [==============================] - 0s 3ms/step - loss: 1.4123 - mse: 191.6133

18/18 [==============================] - 0s 13ms/step - loss: 1.4123 - mse: 191.6133 - val_loss: 1.3993 - val_mse: 188.1761
Epoch 19/100

 1/18 [>.............................] - ETA: 0s - loss: 1.3733 - mse: 189.1457
15/18 [========================>.....] - ETA: 0s - loss: 1.3618 - mse: 190.0781
18/18 [==============================] - 0s 4ms/step - loss: 1.3644 - mse: 191.6134

18/18 [==============================] - 0s 13ms/step - loss: 1.3644 - mse: 191.6134 - val_loss: 1.3521 - val_mse: 188.1762
Epoch 20/100

 1/18 [>.............................] - ETA: 0s - loss: 1.3545 - mse: 200.7570
16/18 [=========================>....] - ETA: 0s - loss: 1.3189 - mse: 191.1172
18/18 [==============================] - 0s 3ms/step - loss: 1.3189 - mse: 191.6135

18/18 [==============================] - 0s 13ms/step - loss: 1.3189 - mse: 191.6135 - val_loss: 1.3099 - val_mse: 188.1763
Epoch 21/100

 1/18 [>.............................] - ETA: 0s - loss: 1.3246 - mse: 195.4204
11/18 [=================>............] - ETA: 0s - loss: 1.2844 - mse: 192.6259
18/18 [==============================] - 0s 5ms/step - loss: 1.2761 - mse: 191.6136

18/18 [==============================] - 0s 14ms/step - loss: 1.2761 - mse: 191.6136 - val_loss: 1.2656 - val_mse: 188.1764
Epoch 22/100

 1/18 [>.............................] - ETA: 0s - loss: 1.3099 - mse: 209.4024
15/18 [========================>.....] - ETA: 0s - loss: 1.2369 - mse: 191.8181
18/18 [==============================] - 0s 4ms/step - loss: 1.2336 - mse: 191.6137

18/18 [==============================] - 0s 13ms/step - loss: 1.2336 - mse: 191.6137 - val_loss: 1.2265 - val_mse: 188.1765
Epoch 23/100

 1/18 [>.............................] - ETA: 0s - loss: 1.1563 - mse: 170.4332
16/18 [=========================>....] - ETA: 0s - loss: 1.1944 - mse: 191.6724
18/18 [==============================] - 0s 3ms/step - loss: 1.1927 - mse: 191.6138

18/18 [==============================] - 0s 13ms/step - loss: 1.1927 - mse: 191.6138 - val_loss: 1.1885 - val_mse: 188.1766
Epoch 24/100

 1/18 [>.............................] - ETA: 0s - loss: 1.1259 - mse: 178.9011
16/18 [=========================>....] - ETA: 0s - loss: 1.1565 - mse: 191.5801
18/18 [==============================] - 0s 3ms/step - loss: 1.1551 - mse: 191.6139

18/18 [==============================] - 0s 12ms/step - loss: 1.1551 - mse: 191.6139 - val_loss: 1.1555 - val_mse: 188.1767
Epoch 25/100

 1/18 [>.............................] - ETA: 0s - loss: 1.0978 - mse: 182.9283
16/18 [=========================>....] - ETA: 0s - loss: 1.1164 - mse: 190.4581
18/18 [==============================] - 0s 4ms/step - loss: 1.1187 - mse: 191.6140

18/18 [==============================] - 0s 13ms/step - loss: 1.1187 - mse: 191.6140 - val_loss: 1.1175 - val_mse: 188.1768
Epoch 26/100

 1/18 [>.............................] - ETA: 0s - loss: 1.0669 - mse: 177.9257
15/18 [========================>.....] - ETA: 0s - loss: 1.0837 - mse: 190.9045
18/18 [==============================] - 0s 4ms/step - loss: 1.0832 - mse: 191.6141

18/18 [==============================] - 0s 13ms/step - loss: 1.0832 - mse: 191.6141 - val_loss: 1.0787 - val_mse: 188.1769
Epoch 27/100

 1/18 [>.............................] - ETA: 0s - loss: 1.0808 - mse: 201.8801
15/18 [========================>.....] - ETA: 0s - loss: 1.0497 - mse: 191.0003
18/18 [==============================] - 0s 4ms/step - loss: 1.0510 - mse: 191.6142

18/18 [==============================] - 0s 13ms/step - loss: 1.0510 - mse: 191.6142 - val_loss: 1.0519 - val_mse: 188.1770
Epoch 28/100

 1/18 [>.............................] - ETA: 0s - loss: 1.0740 - mse: 204.4140
16/18 [=========================>....] - ETA: 0s - loss: 1.0225 - mse: 192.0089
18/18 [==============================] - 0s 3ms/step - loss: 1.0200 - mse: 191.6143

18/18 [==============================] - 0s 12ms/step - loss: 1.0200 - mse: 191.6143 - val_loss: 1.0208 - val_mse: 188.1771
Epoch 29/100

 1/18 [>.............................] - ETA: 0s - loss: 0.9894 - mse: 188.6883
16/18 [=========================>....] - ETA: 0s - loss: 0.9927 - mse: 192.1384
18/18 [==============================] - 0s 3ms/step - loss: 0.9892 - mse: 191.6143

18/18 [==============================] - 0s 12ms/step - loss: 0.9892 - mse: 191.6143 - val_loss: 0.9961 - val_mse: 188.1772
Epoch 30/100

 1/18 [>.............................] - ETA: 0s - loss: 0.9924 - mse: 198.7644
14/18 [======================>.......] - ETA: 0s - loss: 0.9620 - mse: 191.6441
18/18 [==============================] - 0s 4ms/step - loss: 0.9601 - mse: 191.6144

18/18 [==============================] - 0s 13ms/step - loss: 0.9601 - mse: 191.6144 - val_loss: 0.9680 - val_mse: 188.1773
Epoch 31/100

 1/18 [>.............................] - ETA: 0s - loss: 0.9478 - mse: 195.7177
16/18 [=========================>....] - ETA: 0s - loss: 0.9361 - mse: 192.7698
18/18 [==============================] - 0s 3ms/step - loss: 0.9321 - mse: 191.6145

18/18 [==============================] - 0s 13ms/step - loss: 0.9321 - mse: 191.6145 - val_loss: 0.9384 - val_mse: 188.1774
Epoch 32/100

 1/18 [>.............................] - ETA: 0s - loss: 0.8799 - mse: 181.7098
14/18 [======================>.......] - ETA: 0s - loss: 0.9070 - mse: 191.4043
18/18 [==============================] - 0s 4ms/step - loss: 0.9064 - mse: 191.6146

18/18 [==============================] - 0s 14ms/step - loss: 0.9064 - mse: 191.6146 - val_loss: 0.9144 - val_mse: 188.1775
Epoch 33/100

 1/18 [>.............................] - ETA: 0s - loss: 0.9098 - mse: 199.7780
15/18 [========================>.....] - ETA: 0s - loss: 0.8862 - mse: 193.2561
18/18 [==============================] - 0s 4ms/step - loss: 0.8810 - mse: 191.6147

18/18 [==============================] - 0s 13ms/step - loss: 0.8810 - mse: 191.6147 - val_loss: 0.9004 - val_mse: 188.1776
Epoch 34/100

 1/18 [>.............................] - ETA: 0s - loss: 0.8848 - mse: 198.4268
14/18 [======================>.......] - ETA: 0s - loss: 0.8561 - mse: 190.6885
18/18 [==============================] - 0s 4ms/step - loss: 0.8565 - mse: 191.6148

18/18 [==============================] - 0s 14ms/step - loss: 0.8565 - mse: 191.6148 - val_loss: 0.8657 - val_mse: 188.1776
Epoch 35/100

 1/18 [>.............................] - ETA: 0s - loss: 0.8492 - mse: 194.5992
14/18 [======================>.......] - ETA: 0s - loss: 0.8375 - mse: 192.6661
18/18 [==============================] - 0s 4ms/step - loss: 0.8333 - mse: 191.6149

18/18 [==============================] - 0s 13ms/step - loss: 0.8333 - mse: 191.6149 - val_loss: 0.8411 - val_mse: 188.1777
Epoch 36/100

 1/18 [>.............................] - ETA: 0s - loss: 0.8330 - mse: 193.9897
13/18 [====================>.........] - ETA: 0s - loss: 0.8125 - mse: 191.3498
18/18 [==============================] - 0s 4ms/step - loss: 0.8125 - mse: 191.6150

18/18 [==============================] - 0s 15ms/step - loss: 0.8125 - mse: 191.6150 - val_loss: 0.8218 - val_mse: 188.1778
Epoch 37/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7681 - mse: 185.6640
16/18 [=========================>....] - ETA: 0s - loss: 0.7913 - mse: 191.9526
18/18 [==============================] - 0s 3ms/step - loss: 0.7897 - mse: 191.6151

18/18 [==============================] - 0s 13ms/step - loss: 0.7897 - mse: 191.6151 - val_loss: 0.8106 - val_mse: 188.1779
Epoch 38/100

 1/18 [>.............................] - ETA: 0s - loss: 0.8243 - mse: 205.2565
16/18 [=========================>....] - ETA: 0s - loss: 0.7688 - mse: 191.1900
18/18 [==============================] - 0s 3ms/step - loss: 0.7686 - mse: 191.6152

18/18 [==============================] - 0s 13ms/step - loss: 0.7686 - mse: 191.6152 - val_loss: 0.7843 - val_mse: 188.1780
Epoch 39/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7718 - mse: 194.8407
15/18 [========================>.....] - ETA: 0s - loss: 0.7512 - mse: 191.9835
18/18 [==============================] - 0s 4ms/step - loss: 0.7490 - mse: 191.6153

18/18 [==============================] - 0s 13ms/step - loss: 0.7490 - mse: 191.6153 - val_loss: 0.7725 - val_mse: 188.1781
Epoch 40/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7424 - mse: 196.0696
16/18 [=========================>....] - ETA: 0s - loss: 0.7301 - mse: 191.4556
18/18 [==============================] - 0s 3ms/step - loss: 0.7306 - mse: 191.6153

18/18 [==============================] - 0s 13ms/step - loss: 0.7306 - mse: 191.6153 - val_loss: 0.7497 - val_mse: 188.1782
Epoch 41/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7316 - mse: 192.8864
15/18 [========================>.....] - ETA: 0s - loss: 0.7100 - mse: 190.6023
18/18 [==============================] - 0s 4ms/step - loss: 0.7126 - mse: 191.6154

18/18 [==============================] - 0s 13ms/step - loss: 0.7126 - mse: 191.6154 - val_loss: 0.7263 - val_mse: 188.1782
Epoch 42/100

 1/18 [>.............................] - ETA: 0s - loss: 0.7091 - mse: 197.8853
15/18 [========================>.....] - ETA: 0s - loss: 0.6955 - mse: 190.8072
18/18 [==============================] - 0s 4ms/step - loss: 0.6964 - mse: 191.6155

18/18 [==============================] - 0s 13ms/step - loss: 0.6964 - mse: 191.6155 - val_loss: 0.7140 - val_mse: 188.1783
Epoch 43/100

 1/18 [>.............................] - ETA: 0s - loss: 0.6394 - mse: 176.0231
15/18 [========================>.....] - ETA: 0s - loss: 0.6805 - mse: 192.4925
18/18 [==============================] - 0s 4ms/step - loss: 0.6789 - mse: 191.6156

18/18 [==============================] - 0s 13ms/step - loss: 0.6789 - mse: 191.6156 - val_loss: 0.6950 - val_mse: 188.1784
Epoch 44/100

 1/18 [>.............................] - ETA: 0s - loss: 0.6822 - mse: 198.8933
15/18 [========================>.....] - ETA: 0s - loss: 0.6651 - mse: 192.5735
18/18 [==============================] - 0s 4ms/step - loss: 0.6623 - mse: 191.6157

18/18 [==============================] - 0s 13ms/step - loss: 0.6623 - mse: 191.6157 - val_loss: 0.6871 - val_mse: 188.1785
Epoch 45/100

 1/18 [>.............................] - ETA: 0s - loss: 0.6293 - mse: 187.3569
15/18 [========================>.....] - ETA: 0s - loss: 0.6434 - mse: 191.3054
18/18 [==============================] - 0s 4ms/step - loss: 0.6452 - mse: 191.6157

18/18 [==============================] - 0s 13ms/step - loss: 0.6452 - mse: 191.6157 - val_loss: 0.6683 - val_mse: 188.1785
Epoch 46/100

 1/18 [>.............................] - ETA: 0s - loss: 0.6441 - mse: 196.6708
15/18 [========================>.....] - ETA: 0s - loss: 0.6325 - mse: 191.8792
18/18 [==============================] - 0s 4ms/step - loss: 0.6309 - mse: 191.6159

18/18 [==============================] - 0s 13ms/step - loss: 0.6309 - mse: 191.6159 - val_loss: 0.6660 - val_mse: 188.1786
Epoch 47/100

 1/18 [>.............................] - ETA: 0s - loss: 0.6200 - mse: 194.9981
14/18 [======================>.......] - ETA: 0s - loss: 0.6173 - mse: 191.8906
18/18 [==============================] - 0s 4ms/step - loss: 0.6157 - mse: 191.6159

18/18 [==============================] - 0s 13ms/step - loss: 0.6157 - mse: 191.6159 - val_loss: 0.6500 - val_mse: 188.1787
Epoch 48/100

 1/18 [>.............................] - ETA: 0s - loss: 0.6022 - mse: 187.5032
15/18 [========================>.....] - ETA: 0s - loss: 0.6008 - mse: 191.1424
18/18 [==============================] - 0s 4ms/step - loss: 0.6003 - mse: 191.6160

18/18 [==============================] - 0s 13ms/step - loss: 0.6003 - mse: 191.6160 - val_loss: 0.6256 - val_mse: 188.1787
Epoch 49/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5957 - mse: 192.7100
12/18 [===================>..........] - ETA: 0s - loss: 0.5915 - mse: 192.4096
18/18 [==============================] - 0s 4ms/step - loss: 0.5882 - mse: 191.6161

18/18 [==============================] - 0s 14ms/step - loss: 0.5882 - mse: 191.6161 - val_loss: 0.6140 - val_mse: 188.1788
Epoch 50/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5600 - mse: 183.9595
15/18 [========================>.....] - ETA: 0s - loss: 0.5761 - mse: 191.4044
18/18 [==============================] - 0s 4ms/step - loss: 0.5759 - mse: 191.6161

18/18 [==============================] - 0s 14ms/step - loss: 0.5759 - mse: 191.6161 - val_loss: 0.6252 - val_mse: 188.1789
Epoch 51/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5848 - mse: 196.2495
12/18 [===================>..........] - ETA: 0s - loss: 0.5633 - mse: 192.2486
18/18 [==============================] - 0s 5ms/step - loss: 0.5629 - mse: 191.6162

18/18 [==============================] - 0s 16ms/step - loss: 0.5629 - mse: 191.6162 - val_loss: 0.5896 - val_mse: 188.1790
Epoch 52/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5417 - mse: 197.8758
11/18 [=================>............] - ETA: 0s - loss: 0.5550 - mse: 192.9500
18/18 [==============================] - 0s 5ms/step - loss: 0.5491 - mse: 191.6163

18/18 [==============================] - 0s 14ms/step - loss: 0.5491 - mse: 191.6163 - val_loss: 0.5808 - val_mse: 188.1790
Epoch 53/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5277 - mse: 187.5607
15/18 [========================>.....] - ETA: 0s - loss: 0.5353 - mse: 190.7389
18/18 [==============================] - 0s 4ms/step - loss: 0.5379 - mse: 191.6163

18/18 [==============================] - 0s 13ms/step - loss: 0.5379 - mse: 191.6163 - val_loss: 0.5773 - val_mse: 188.1791
Epoch 54/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4774 - mse: 170.7576
16/18 [=========================>....] - ETA: 0s - loss: 0.5263 - mse: 191.7084
18/18 [==============================] - 0s 4ms/step - loss: 0.5255 - mse: 191.6164

18/18 [==============================] - 0s 13ms/step - loss: 0.5255 - mse: 191.6164 - val_loss: 0.5560 - val_mse: 188.1792
Epoch 55/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5110 - mse: 191.1103
14/18 [======================>.......] - ETA: 0s - loss: 0.5152 - mse: 191.1697
18/18 [==============================] - 0s 4ms/step - loss: 0.5146 - mse: 191.6165

18/18 [==============================] - 0s 14ms/step - loss: 0.5146 - mse: 191.6165 - val_loss: 0.5506 - val_mse: 188.1792
Epoch 56/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4963 - mse: 191.7967
11/18 [=================>............] - ETA: 0s - loss: 0.5028 - mse: 190.7228
18/18 [==============================] - 0s 5ms/step - loss: 0.5037 - mse: 191.6165

18/18 [==============================] - 0s 14ms/step - loss: 0.5037 - mse: 191.6165 - val_loss: 0.5476 - val_mse: 188.1793
Epoch 57/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5345 - mse: 201.2562
12/18 [===================>..........] - ETA: 0s - loss: 0.4979 - mse: 192.5446
18/18 [==============================] - 0s 4ms/step - loss: 0.4935 - mse: 191.6166

18/18 [==============================] - 0s 14ms/step - loss: 0.4935 - mse: 191.6166 - val_loss: 0.5301 - val_mse: 188.1794
Epoch 58/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4629 - mse: 186.2027
15/18 [========================>.....] - ETA: 0s - loss: 0.4835 - mse: 191.1142
18/18 [==============================] - 0s 4ms/step - loss: 0.4839 - mse: 191.6167

18/18 [==============================] - 0s 13ms/step - loss: 0.4839 - mse: 191.6167 - val_loss: 0.5232 - val_mse: 188.1794
Epoch 59/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4750 - mse: 195.7697
16/18 [=========================>....] - ETA: 0s - loss: 0.4741 - mse: 191.2572
18/18 [==============================] - 0s 3ms/step - loss: 0.4743 - mse: 191.6167

18/18 [==============================] - 0s 13ms/step - loss: 0.4743 - mse: 191.6167 - val_loss: 0.5277 - val_mse: 188.1795
Epoch 60/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4580 - mse: 188.0171
14/18 [======================>.......] - ETA: 0s - loss: 0.4662 - mse: 192.3248
18/18 [==============================] - 0s 4ms/step - loss: 0.4652 - mse: 191.6168

18/18 [==============================] - 0s 14ms/step - loss: 0.4652 - mse: 191.6168 - val_loss: 0.5094 - val_mse: 188.1795
Epoch 61/100

 1/18 [>.............................] - ETA: 0s - loss: 0.5034 - mse: 204.3093
15/18 [========================>.....] - ETA: 0s - loss: 0.4561 - mse: 192.1764
18/18 [==============================] - 0s 4ms/step - loss: 0.4553 - mse: 191.6169

18/18 [==============================] - 0s 13ms/step - loss: 0.4553 - mse: 191.6169 - val_loss: 0.5099 - val_mse: 188.1796
Epoch 62/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4551 - mse: 195.0801
16/18 [=========================>....] - ETA: 0s - loss: 0.4500 - mse: 192.1879
18/18 [==============================] - 0s 4ms/step - loss: 0.4479 - mse: 191.6169

18/18 [==============================] - 0s 13ms/step - loss: 0.4479 - mse: 191.6169 - val_loss: 0.4815 - val_mse: 188.1796
Epoch 63/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4541 - mse: 194.4529
14/18 [======================>.......] - ETA: 0s - loss: 0.4383 - mse: 190.5857
18/18 [==============================] - 0s 4ms/step - loss: 0.4395 - mse: 191.6170

18/18 [==============================] - 0s 13ms/step - loss: 0.4395 - mse: 191.6170 - val_loss: 0.5078 - val_mse: 188.1797
Epoch 64/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4668 - mse: 195.0206
16/18 [=========================>....] - ETA: 0s - loss: 0.4312 - mse: 190.4350
18/18 [==============================] - 0s 3ms/step - loss: 0.4336 - mse: 191.6170

18/18 [==============================] - 0s 13ms/step - loss: 0.4336 - mse: 191.6170 - val_loss: 0.4829 - val_mse: 188.1797
Epoch 65/100

 1/18 [>.............................] - ETA: 0s - loss: 0.4049 - mse: 184.6863
12/18 [===================>..........] - ETA: 0s - loss: 0.4194 - mse: 189.4916
18/18 [==============================] - 0s 5ms/step - loss: 0.4234 - mse: 191.6171

18/18 [==============================] - 0s 15ms/step - loss: 0.4234 - mse: 191.6171 - val_loss: 0.4590 - val_mse: 188.1798
Epoch 66/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3994 - mse: 188.4995
16/18 [=========================>....] - ETA: 0s - loss: 0.4180 - mse: 192.4927
18/18 [==============================] - 0s 3ms/step - loss: 0.4153 - mse: 191.6172

18/18 [==============================] - 0s 13ms/step - loss: 0.4153 - mse: 191.6172 - val_loss: 0.4681 - val_mse: 188.1798
Epoch 67/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3750 - mse: 179.6075
16/18 [=========================>....] - ETA: 0s - loss: 0.4069 - mse: 191.4472
18/18 [==============================] - 0s 3ms/step - loss: 0.4080 - mse: 191.6172

18/18 [==============================] - 0s 12ms/step - loss: 0.4080 - mse: 191.6172 - val_loss: 0.4703 - val_mse: 188.1799
Epoch 68/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3839 - mse: 187.1941
15/18 [========================>.....] - ETA: 0s - loss: 0.3987 - mse: 191.8390
18/18 [==============================] - 0s 4ms/step - loss: 0.3997 - mse: 191.6173

18/18 [==============================] - 0s 13ms/step - loss: 0.3997 - mse: 191.6173 - val_loss: 0.4632 - val_mse: 188.1799
Epoch 69/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3916 - mse: 191.1142
15/18 [========================>.....] - ETA: 0s - loss: 0.3944 - mse: 191.8763
18/18 [==============================] - 0s 4ms/step - loss: 0.3936 - mse: 191.6173

18/18 [==============================] - 0s 13ms/step - loss: 0.3936 - mse: 191.6173 - val_loss: 0.4454 - val_mse: 188.1800
Epoch 70/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3753 - mse: 186.9318
14/18 [======================>.......] - ETA: 0s - loss: 0.3900 - mse: 191.3559
18/18 [==============================] - 0s 4ms/step - loss: 0.3877 - mse: 191.6173

18/18 [==============================] - 0s 13ms/step - loss: 0.3877 - mse: 191.6173 - val_loss: 0.4338 - val_mse: 188.1800
Epoch 71/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3750 - mse: 187.2367
15/18 [========================>.....] - ETA: 0s - loss: 0.3758 - mse: 190.5232
18/18 [==============================] - 0s 4ms/step - loss: 0.3780 - mse: 191.6174

18/18 [==============================] - 0s 13ms/step - loss: 0.3780 - mse: 191.6174 - val_loss: 0.4439 - val_mse: 188.1801
Epoch 72/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3709 - mse: 191.8340
16/18 [=========================>....] - ETA: 0s - loss: 0.3738 - mse: 192.0574
18/18 [==============================] - 0s 3ms/step - loss: 0.3729 - mse: 191.6174

18/18 [==============================] - 0s 12ms/step - loss: 0.3729 - mse: 191.6174 - val_loss: 0.4287 - val_mse: 188.1801
Epoch 73/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3820 - mse: 200.1314
16/18 [=========================>....] - ETA: 0s - loss: 0.3650 - mse: 190.6653
18/18 [==============================] - 0s 4ms/step - loss: 0.3667 - mse: 191.6175

18/18 [==============================] - 0s 13ms/step - loss: 0.3667 - mse: 191.6175 - val_loss: 0.4231 - val_mse: 188.1802
Epoch 74/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3611 - mse: 191.2033
12/18 [===================>..........] - ETA: 0s - loss: 0.3642 - mse: 192.5676
18/18 [==============================] - 0s 5ms/step - loss: 0.3603 - mse: 191.6175

18/18 [==============================] - 0s 14ms/step - loss: 0.3603 - mse: 191.6175 - val_loss: 0.4203 - val_mse: 188.1802
Epoch 75/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3596 - mse: 197.8071
14/18 [======================>.......] - ETA: 0s - loss: 0.3553 - mse: 192.0541
18/18 [==============================] - 0s 4ms/step - loss: 0.3537 - mse: 191.6176

18/18 [==============================] - 0s 14ms/step - loss: 0.3537 - mse: 191.6176 - val_loss: 0.4307 - val_mse: 188.1803
Epoch 76/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3424 - mse: 187.8435
15/18 [========================>.....] - ETA: 0s - loss: 0.3476 - mse: 190.9706
18/18 [==============================] - 0s 4ms/step - loss: 0.3484 - mse: 191.6176

18/18 [==============================] - 0s 13ms/step - loss: 0.3484 - mse: 191.6176 - val_loss: 0.3947 - val_mse: 188.1803
Epoch 77/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3356 - mse: 187.0973
15/18 [========================>.....] - ETA: 0s - loss: 0.3414 - mse: 191.4705
18/18 [==============================] - 0s 4ms/step - loss: 0.3434 - mse: 191.6176

18/18 [==============================] - 0s 13ms/step - loss: 0.3434 - mse: 191.6176 - val_loss: 0.4130 - val_mse: 188.1803
Epoch 78/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3442 - mse: 191.5164
14/18 [======================>.......] - ETA: 0s - loss: 0.3379 - mse: 191.4684
18/18 [==============================] - 0s 4ms/step - loss: 0.3373 - mse: 191.6177

18/18 [==============================] - 0s 13ms/step - loss: 0.3373 - mse: 191.6177 - val_loss: 0.3991 - val_mse: 188.1803
Epoch 79/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3294 - mse: 193.2053
16/18 [=========================>....] - ETA: 0s - loss: 0.3310 - mse: 191.3715
18/18 [==============================] - 0s 3ms/step - loss: 0.3320 - mse: 191.6177

18/18 [==============================] - 0s 13ms/step - loss: 0.3320 - mse: 191.6177 - val_loss: 0.4123 - val_mse: 188.1804
Epoch 80/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3419 - mse: 197.6556
16/18 [=========================>....] - ETA: 0s - loss: 0.3233 - mse: 189.9644
18/18 [==============================] - 0s 3ms/step - loss: 0.3265 - mse: 191.6178

18/18 [==============================] - 0s 12ms/step - loss: 0.3265 - mse: 191.6178 - val_loss: 0.3844 - val_mse: 188.1804
Epoch 81/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3228 - mse: 186.1104
16/18 [=========================>....] - ETA: 0s - loss: 0.3201 - mse: 191.6254
18/18 [==============================] - 0s 3ms/step - loss: 0.3211 - mse: 191.6178

18/18 [==============================] - 0s 12ms/step - loss: 0.3211 - mse: 191.6178 - val_loss: 0.3805 - val_mse: 188.1805
Epoch 82/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3432 - mse: 201.0708
16/18 [=========================>....] - ETA: 0s - loss: 0.3162 - mse: 190.9524
18/18 [==============================] - 0s 3ms/step - loss: 0.3166 - mse: 191.6178

18/18 [==============================] - 0s 13ms/step - loss: 0.3166 - mse: 191.6178 - val_loss: 0.3878 - val_mse: 188.1805
Epoch 83/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2854 - mse: 179.4344
16/18 [=========================>....] - ETA: 0s - loss: 0.3121 - mse: 190.9804
18/18 [==============================] - 0s 3ms/step - loss: 0.3130 - mse: 191.6179

18/18 [==============================] - 0s 13ms/step - loss: 0.3130 - mse: 191.6179 - val_loss: 0.4180 - val_mse: 188.1805
Epoch 84/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3127 - mse: 186.2263
16/18 [=========================>....] - ETA: 0s - loss: 0.3139 - mse: 192.0956
18/18 [==============================] - 0s 3ms/step - loss: 0.3124 - mse: 191.6179

18/18 [==============================] - 0s 13ms/step - loss: 0.3124 - mse: 191.6179 - val_loss: 0.3626 - val_mse: 188.1806
Epoch 85/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3110 - mse: 201.0091
16/18 [=========================>....] - ETA: 0s - loss: 0.3048 - mse: 191.7295
18/18 [==============================] - 0s 3ms/step - loss: 0.3042 - mse: 191.6180

18/18 [==============================] - 0s 12ms/step - loss: 0.3042 - mse: 191.6180 - val_loss: 0.3556 - val_mse: 188.1806
Epoch 86/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3315 - mse: 203.0012
16/18 [=========================>....] - ETA: 0s - loss: 0.2995 - mse: 192.0455
18/18 [==============================] - 0s 3ms/step - loss: 0.2975 - mse: 191.6180

18/18 [==============================] - 0s 13ms/step - loss: 0.2975 - mse: 191.6180 - val_loss: 0.3683 - val_mse: 188.1806
Epoch 87/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2759 - mse: 191.2146
16/18 [=========================>....] - ETA: 0s - loss: 0.2922 - mse: 191.8131
18/18 [==============================] - 0s 3ms/step - loss: 0.2914 - mse: 191.6180

18/18 [==============================] - 0s 13ms/step - loss: 0.2914 - mse: 191.6180 - val_loss: 0.3663 - val_mse: 188.1806
Epoch 88/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2986 - mse: 195.3946
16/18 [=========================>....] - ETA: 0s - loss: 0.2870 - mse: 191.6824
18/18 [==============================] - 0s 3ms/step - loss: 0.2871 - mse: 191.6181

18/18 [==============================] - 0s 12ms/step - loss: 0.2871 - mse: 191.6181 - val_loss: 0.3589 - val_mse: 188.1807
Epoch 89/100

 1/18 [>.............................] - ETA: 0s - loss: 0.3137 - mse: 201.9355
16/18 [=========================>....] - ETA: 0s - loss: 0.2821 - mse: 191.1266
18/18 [==============================] - 0s 3ms/step - loss: 0.2833 - mse: 191.6181

18/18 [==============================] - 0s 12ms/step - loss: 0.2833 - mse: 191.6181 - val_loss: 0.3605 - val_mse: 188.1807
Epoch 90/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2865 - mse: 196.9882
16/18 [=========================>....] - ETA: 0s - loss: 0.2800 - mse: 191.8539
18/18 [==============================] - 0s 3ms/step - loss: 0.2801 - mse: 191.6181

18/18 [==============================] - 0s 13ms/step - loss: 0.2801 - mse: 191.6181 - val_loss: 0.3604 - val_mse: 188.1807
Epoch 91/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2904 - mse: 203.6398
10/18 [===============>..............] - ETA: 0s - loss: 0.2704 - mse: 190.6983
18/18 [==============================] - 0s 5ms/step - loss: 0.2751 - mse: 191.6182

18/18 [==============================] - 0s 14ms/step - loss: 0.2751 - mse: 191.6182 - val_loss: 0.3568 - val_mse: 188.1807
Epoch 92/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2524 - mse: 180.1981
15/18 [========================>.....] - ETA: 0s - loss: 0.2704 - mse: 190.6760
18/18 [==============================] - 0s 4ms/step - loss: 0.2715 - mse: 191.6182

18/18 [==============================] - 0s 13ms/step - loss: 0.2715 - mse: 191.6182 - val_loss: 0.3303 - val_mse: 188.1808
Epoch 93/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2843 - mse: 193.6101
15/18 [========================>.....] - ETA: 0s - loss: 0.2652 - mse: 191.0661
18/18 [==============================] - 0s 4ms/step - loss: 0.2676 - mse: 191.6182

18/18 [==============================] - 0s 13ms/step - loss: 0.2676 - mse: 191.6182 - val_loss: 0.3461 - val_mse: 188.1808
Epoch 94/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2861 - mse: 201.7475
16/18 [=========================>....] - ETA: 0s - loss: 0.2632 - mse: 191.5389
18/18 [==============================] - 0s 3ms/step - loss: 0.2632 - mse: 191.6182

18/18 [==============================] - 0s 12ms/step - loss: 0.2632 - mse: 191.6182 - val_loss: 0.3515 - val_mse: 188.1809
Epoch 95/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2512 - mse: 198.1490
16/18 [=========================>....] - ETA: 0s - loss: 0.2593 - mse: 190.5227
18/18 [==============================] - 0s 3ms/step - loss: 0.2607 - mse: 191.6183

18/18 [==============================] - 0s 12ms/step - loss: 0.2607 - mse: 191.6183 - val_loss: 0.3531 - val_mse: 188.1809
Epoch 96/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2659 - mse: 197.7853
16/18 [=========================>....] - ETA: 0s - loss: 0.2554 - mse: 191.3409
18/18 [==============================] - 0s 3ms/step - loss: 0.2557 - mse: 191.6183

18/18 [==============================] - 0s 12ms/step - loss: 0.2557 - mse: 191.6183 - val_loss: 0.3508 - val_mse: 188.1809
Epoch 97/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2595 - mse: 189.6599
16/18 [=========================>....] - ETA: 0s - loss: 0.2512 - mse: 191.2171
18/18 [==============================] - 0s 3ms/step - loss: 0.2531 - mse: 191.6183

18/18 [==============================] - 0s 12ms/step - loss: 0.2531 - mse: 191.6183 - val_loss: 0.3305 - val_mse: 188.1809
Epoch 98/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2491 - mse: 192.0601
16/18 [=========================>....] - ETA: 0s - loss: 0.2494 - mse: 191.6835
18/18 [==============================] - 0s 3ms/step - loss: 0.2497 - mse: 191.6183

18/18 [==============================] - 0s 12ms/step - loss: 0.2497 - mse: 191.6183 - val_loss: 0.3412 - val_mse: 188.1809
Epoch 99/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2620 - mse: 200.0634
16/18 [=========================>....] - ETA: 0s - loss: 0.2463 - mse: 192.4228
18/18 [==============================] - 0s 3ms/step - loss: 0.2451 - mse: 191.6184

18/18 [==============================] - 0s 12ms/step - loss: 0.2451 - mse: 191.6184 - val_loss: 0.3461 - val_mse: 188.1810
Epoch 100/100

 1/18 [>.............................] - ETA: 0s - loss: 0.2498 - mse: 194.9894
16/18 [=========================>....] - ETA: 0s - loss: 0.2439 - mse: 192.0877
18/18 [==============================] - 0s 3ms/step - loss: 0.2427 - mse: 191.6184

18/18 [==============================] - 0s 12ms/step - loss: 0.2427 - mse: 191.6184 - val_loss: 0.3382 - val_mse: 188.1810

Run completed: runs/2023-04-03T22-34-27Z

Training run 9/9 (flags = list(128, 0.001, 200, 30, "relu")) 
Using run directory runs/2023-04-03T22-34-51Z

> FLAGS <- flags(
+   flag_numeric("nodes", 120),
+   flag_numeric("batch_size", 100),
+   flag_string("activation", "relu"),
+   flag_numeric("learni ..." ... [TRUNCATED] 

> model = keras_model_sequential()

> model %>%
+   layer_dense(units = FLAGS$nodes, activation = FLAGS$activation, input_shape = 106) %>%
+   layer_dense(units = FLAGS$nodes, activation .... [TRUNCATED] 

> model %>% compile(
+   optimizer = optimizer_adam(lr = FLAGS$learning_rate),
+   loss = 'sparse_categorical_crossentropy',
+   metrics = c('mse')
+  .... [TRUNCATED] 

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

> model %>% fit(
+   second_bikes_matrix, second_bikes_train_set$count, epochs = FLAGS$epochs, batch_size = FLAGS$batch_size, validation_data = list(a .... [TRUNCATED] 
Epoch 1/30

 1/45 [..............................] - ETA: 13s - loss: 4.9079 - mse: 192.0634
15/45 [=========>....................] - ETA: 0s - loss: 4.1399 - mse: 189.5280 
29/45 [==================>...........] - ETA: 0s - loss: 3.7301 - mse: 190.4093
43/45 [===========================>..] - ETA: 0s - loss: 3.4621 - mse: 191.1103
45/45 [==============================] - 0s 4ms/step - loss: 3.4450 - mse: 191.6117

45/45 [==============================] - 1s 18ms/step - loss: 3.4450 - mse: 191.6117 - val_loss: 2.6945 - val_mse: 188.1749
Epoch 2/30

 1/45 [..............................] - ETA: 0s - loss: 2.6721 - mse: 197.4094
13/45 [=======>......................] - ETA: 0s - loss: 2.5944 - mse: 189.4183
26/45 [================>.............] - ETA: 0s - loss: 2.5015 - mse: 193.1644
40/45 [=========================>....] - ETA: 0s - loss: 2.4060 - mse: 191.9846
45/45 [==============================] - 0s 4ms/step - loss: 2.3818 - mse: 191.6123

45/45 [==============================] - 0s 7ms/step - loss: 2.3818 - mse: 191.6123 - val_loss: 2.1753 - val_mse: 188.1754
Epoch 3/30

 1/45 [..............................] - ETA: 0s - loss: 2.1156 - mse: 193.7051
14/45 [========>.....................] - ETA: 0s - loss: 2.0444 - mse: 194.8060
28/45 [=================>............] - ETA: 0s - loss: 1.9863 - mse: 190.7948
41/45 [==========================>...] - ETA: 0s - loss: 1.9402 - mse: 192.3318
45/45 [==============================] - 0s 4ms/step - loss: 1.9270 - mse: 191.6127

45/45 [==============================] - 0s 7ms/step - loss: 1.9270 - mse: 191.6127 - val_loss: 1.8462 - val_mse: 188.1758
Epoch 4/30

 1/45 [..............................] - ETA: 0s - loss: 1.8260 - mse: 186.5400
13/45 [=======>......................] - ETA: 0s - loss: 1.7504 - mse: 188.6111
25/45 [===============>..............] - ETA: 0s - loss: 1.7162 - mse: 191.2743
37/45 [=======================>......] - ETA: 0s - loss: 1.6837 - mse: 191.9132
45/45 [==============================] - 0s 4ms/step - loss: 1.6594 - mse: 191.6132

45/45 [==============================] - 0s 8ms/step - loss: 1.6594 - mse: 191.6132 - val_loss: 1.6180 - val_mse: 188.1763
Epoch 5/30

 1/45 [..............................] - ETA: 0s - loss: 1.5893 - mse: 215.2976
13/45 [=======>......................] - ETA: 0s - loss: 1.4978 - mse: 187.4991
25/45 [===============>..............] - ETA: 0s - loss: 1.4778 - mse: 192.6940
37/45 [=======================>......] - ETA: 0s - loss: 1.4581 - mse: 191.9998
45/45 [==============================] - 0s 4ms/step - loss: 1.4442 - mse: 191.6135

45/45 [==============================] - 0s 8ms/step - loss: 1.4442 - mse: 191.6135 - val_loss: 1.3880 - val_mse: 188.1765
Epoch 6/30

 1/45 [..............................] - ETA: 0s - loss: 1.3318 - mse: 191.3692
13/45 [=======>......................] - ETA: 0s - loss: 1.3409 - mse: 192.9583
26/45 [================>.............] - ETA: 0s - loss: 1.3091 - mse: 193.1084
39/45 [=========================>....] - ETA: 0s - loss: 1.2825 - mse: 192.3782
45/45 [==============================] - 0s 4ms/step - loss: 1.2736 - mse: 191.6138

45/45 [==============================] - 0s 7ms/step - loss: 1.2736 - mse: 191.6138 - val_loss: 1.2516 - val_mse: 188.1767
Epoch 7/30

 1/45 [..............................] - ETA: 0s - loss: 1.1116 - mse: 179.7459
13/45 [=======>......................] - ETA: 0s - loss: 1.1933 - mse: 194.9452
27/45 [=================>............] - ETA: 0s - loss: 1.1677 - mse: 191.9758
40/45 [=========================>....] - ETA: 0s - loss: 1.1540 - mse: 191.7646
45/45 [==============================] - 0s 4ms/step - loss: 1.1473 - mse: 191.6142

45/45 [==============================] - 0s 8ms/step - loss: 1.1473 - mse: 191.6142 - val_loss: 1.1615 - val_mse: 188.1772
Epoch 8/30

 1/45 [..............................] - ETA: 0s - loss: 1.0571 - mse: 181.1559
14/45 [========>.....................] - ETA: 0s - loss: 1.0733 - mse: 191.8486
26/45 [================>.............] - ETA: 0s - loss: 1.0526 - mse: 190.3730
36/45 [=======================>......] - ETA: 0s - loss: 1.0438 - mse: 190.4767
45/45 [==============================] - 0s 4ms/step - loss: 1.0363 - mse: 191.6145

45/45 [==============================] - 0s 8ms/step - loss: 1.0363 - mse: 191.6145 - val_loss: 1.0838 - val_mse: 188.1775
Epoch 9/30

 1/45 [..............................] - ETA: 0s - loss: 0.9448 - mse: 161.6039
13/45 [=======>......................] - ETA: 0s - loss: 0.9803 - mse: 191.9312
27/45 [=================>............] - ETA: 0s - loss: 0.9691 - mse: 193.0677
41/45 [==========================>...] - ETA: 0s - loss: 0.9407 - mse: 191.2822
45/45 [==============================] - 0s 4ms/step - loss: 0.9392 - mse: 191.6147

45/45 [==============================] - 0s 7ms/step - loss: 0.9392 - mse: 191.6147 - val_loss: 0.9528 - val_mse: 188.1776
Epoch 10/30

 1/45 [..............................] - ETA: 0s - loss: 0.8458 - mse: 195.6386
15/45 [=========>....................] - ETA: 0s - loss: 0.8734 - mse: 186.3830
29/45 [==================>...........] - ETA: 0s - loss: 0.8668 - mse: 188.5057
43/45 [===========================>..] - ETA: 0s - loss: 0.8589 - mse: 191.2451
45/45 [==============================] - 0s 4ms/step - loss: 0.8591 - mse: 191.6150

45/45 [==============================] - 0s 7ms/step - loss: 0.8591 - mse: 191.6150 - val_loss: 0.9024 - val_mse: 188.1780
Epoch 11/30

 1/45 [..............................] - ETA: 0s - loss: 0.7973 - mse: 171.2433
14/45 [========>.....................] - ETA: 0s - loss: 0.8459 - mse: 194.7972
27/45 [=================>............] - ETA: 0s - loss: 0.8199 - mse: 192.2156
39/45 [=========================>....] - ETA: 0s - loss: 0.8038 - mse: 191.8966
45/45 [==============================] - 0s 4ms/step - loss: 0.7975 - mse: 191.6153

45/45 [==============================] - 0s 8ms/step - loss: 0.7975 - mse: 191.6153 - val_loss: 0.8789 - val_mse: 188.1782
Epoch 12/30

 1/45 [..............................] - ETA: 0s - loss: 0.7728 - mse: 201.2441
15/45 [=========>....................] - ETA: 0s - loss: 0.7817 - mse: 191.3756
29/45 [==================>...........] - ETA: 0s - loss: 0.7673 - mse: 190.7393
43/45 [===========================>..] - ETA: 0s - loss: 0.7519 - mse: 191.7404
45/45 [==============================] - 0s 4ms/step - loss: 0.7500 - mse: 191.6156

45/45 [==============================] - 0s 8ms/step - loss: 0.7500 - mse: 191.6156 - val_loss: 0.8094 - val_mse: 188.1783
Epoch 13/30

 1/45 [..............................] - ETA: 0s - loss: 0.7782 - mse: 209.9356
12/45 [=======>......................] - ETA: 0s - loss: 0.7137 - mse: 194.5185
24/45 [===============>..............] - ETA: 0s - loss: 0.6999 - mse: 191.6802
38/45 [========================>.....] - ETA: 0s - loss: 0.6926 - mse: 193.0582
45/45 [==============================] - 0s 4ms/step - loss: 0.6868 - mse: 191.6158

45/45 [==============================] - 0s 8ms/step - loss: 0.6868 - mse: 191.6158 - val_loss: 0.8454 - val_mse: 188.1786
Epoch 14/30

 1/45 [..............................] - ETA: 0s - loss: 0.7029 - mse: 204.0896
10/45 [=====>........................] - ETA: 0s - loss: 0.7028 - mse: 193.3823
20/45 [============>.................] - ETA: 0s - loss: 0.6910 - mse: 192.8345
32/45 [====================>.........] - ETA: 0s - loss: 0.6758 - mse: 192.2651
45/45 [==============================] - 0s 5ms/step - loss: 0.6651 - mse: 191.6160

45/45 [==============================] - 0s 8ms/step - loss: 0.6651 - mse: 191.6160 - val_loss: 0.7032 - val_mse: 188.1788
Epoch 15/30

 1/45 [..............................] - ETA: 0s - loss: 0.5530 - mse: 162.4711
15/45 [=========>....................] - ETA: 0s - loss: 0.6275 - mse: 187.7190
29/45 [==================>...........] - ETA: 0s - loss: 0.6188 - mse: 191.6841
43/45 [===========================>..] - ETA: 0s - loss: 0.6119 - mse: 191.8660
45/45 [==============================] - 0s 4ms/step - loss: 0.6121 - mse: 191.6162

45/45 [==============================] - 0s 7ms/step - loss: 0.6121 - mse: 191.6162 - val_loss: 0.7049 - val_mse: 188.1790
Epoch 16/30

 1/45 [..............................] - ETA: 0s - loss: 0.5365 - mse: 175.7469
11/45 [======>.......................] - ETA: 0s - loss: 0.6011 - mse: 188.7817
22/45 [=============>................] - ETA: 0s - loss: 0.5966 - mse: 189.5406
34/45 [=====================>........] - ETA: 0s - loss: 0.5941 - mse: 191.9430
45/45 [==============================] - 0s 4ms/step - loss: 0.5903 - mse: 191.6164

45/45 [==============================] - 0s 8ms/step - loss: 0.5903 - mse: 191.6164 - val_loss: 0.6816 - val_mse: 188.1793
Epoch 17/30

 1/45 [..............................] - ETA: 0s - loss: 0.5675 - mse: 175.0755
13/45 [=======>......................] - ETA: 0s - loss: 0.6125 - mse: 190.6241
24/45 [===============>..............] - ETA: 0s - loss: 0.5928 - mse: 191.2582
35/45 [======================>.......] - ETA: 0s - loss: 0.5831 - mse: 191.4319
45/45 [==============================] - 0s 5ms/step - loss: 0.5746 - mse: 191.6165

45/45 [==============================] - 0s 8ms/step - loss: 0.5746 - mse: 191.6165 - val_loss: 0.6276 - val_mse: 188.1793
Epoch 18/30

 1/45 [..............................] - ETA: 0s - loss: 0.6409 - mse: 211.2921
15/45 [=========>....................] - ETA: 0s - loss: 0.5429 - mse: 194.8555
29/45 [==================>...........] - ETA: 0s - loss: 0.5236 - mse: 194.4378
43/45 [===========================>..] - ETA: 0s - loss: 0.5111 - mse: 191.5856
45/45 [==============================] - 0s 4ms/step - loss: 0.5112 - mse: 191.6166

45/45 [==============================] - 0s 8ms/step - loss: 0.5112 - mse: 191.6166 - val_loss: 0.6316 - val_mse: 188.1794
Epoch 19/30

 1/45 [..............................] - ETA: 0s - loss: 0.4644 - mse: 177.2573
13/45 [=======>......................] - ETA: 0s - loss: 0.4821 - mse: 186.9456
27/45 [=================>............] - ETA: 0s - loss: 0.4929 - mse: 193.4655
41/45 [==========================>...] - ETA: 0s - loss: 0.4842 - mse: 192.8212
45/45 [==============================] - 0s 4ms/step - loss: 0.4820 - mse: 191.6168

45/45 [==============================] - 0s 7ms/step - loss: 0.4820 - mse: 191.6168 - val_loss: 0.5435 - val_mse: 188.1795
Epoch 20/30

 1/45 [..............................] - ETA: 0s - loss: 0.4730 - mse: 197.3055
14/45 [========>.....................] - ETA: 0s - loss: 0.5052 - mse: 196.1804
28/45 [=================>............] - ETA: 0s - loss: 0.4899 - mse: 192.2572
41/45 [==========================>...] - ETA: 0s - loss: 0.4789 - mse: 191.4612
45/45 [==============================] - 0s 4ms/step - loss: 0.4779 - mse: 191.6170

45/45 [==============================] - 0s 7ms/step - loss: 0.4779 - mse: 191.6170 - val_loss: 0.5354 - val_mse: 188.1796
Epoch 21/30

 1/45 [..............................] - ETA: 0s - loss: 0.4316 - mse: 185.4990
15/45 [=========>....................] - ETA: 0s - loss: 0.4793 - mse: 193.6606
29/45 [==================>...........] - ETA: 0s - loss: 0.4581 - mse: 192.1801
43/45 [===========================>..] - ETA: 0s - loss: 0.4481 - mse: 191.3931
45/45 [==============================] - 0s 4ms/step - loss: 0.4476 - mse: 191.6171

45/45 [==============================] - 0s 7ms/step - loss: 0.4476 - mse: 191.6171 - val_loss: 0.5261 - val_mse: 188.1798
Epoch 22/30

 1/45 [..............................] - ETA: 0s - loss: 0.4271 - mse: 187.5450
15/45 [=========>....................] - ETA: 0s - loss: 0.4462 - mse: 194.8501
29/45 [==================>...........] - ETA: 0s - loss: 0.4367 - mse: 192.8912
43/45 [===========================>..] - ETA: 0s - loss: 0.4274 - mse: 192.1292
45/45 [==============================] - 0s 4ms/step - loss: 0.4261 - mse: 191.6172

45/45 [==============================] - 0s 7ms/step - loss: 0.4261 - mse: 191.6172 - val_loss: 0.5154 - val_mse: 188.1799
Epoch 23/30

 1/45 [..............................] - ETA: 0s - loss: 0.4178 - mse: 197.4841
11/45 [======>.......................] - ETA: 0s - loss: 0.4328 - mse: 193.6980
22/45 [=============>................] - ETA: 0s - loss: 0.4180 - mse: 192.6498
33/45 [=====================>........] - ETA: 0s - loss: 0.4096 - mse: 191.2882
45/45 [==============================] - 0s 5ms/step - loss: 0.4093 - mse: 191.6173

45/45 [==============================] - 0s 8ms/step - loss: 0.4093 - mse: 191.6173 - val_loss: 0.4584 - val_mse: 188.1799
Epoch 24/30

 1/45 [..............................] - ETA: 0s - loss: 0.3884 - mse: 184.5896
15/45 [=========>....................] - ETA: 0s - loss: 0.4064 - mse: 189.9944
29/45 [==================>...........] - ETA: 0s - loss: 0.4030 - mse: 191.1697
43/45 [===========================>..] - ETA: 0s - loss: 0.3949 - mse: 191.5296
45/45 [==============================] - 0s 4ms/step - loss: 0.3944 - mse: 191.6174

45/45 [==============================] - 0s 7ms/step - loss: 0.3944 - mse: 191.6174 - val_loss: 0.4973 - val_mse: 188.1801
Epoch 25/30

 1/45 [..............................] - ETA: 0s - loss: 0.3818 - mse: 187.6721
15/45 [=========>....................] - ETA: 0s - loss: 0.3906 - mse: 193.5516
29/45 [==================>...........] - ETA: 0s - loss: 0.3803 - mse: 192.5552
43/45 [===========================>..] - ETA: 0s - loss: 0.3722 - mse: 191.6684
45/45 [==============================] - 0s 4ms/step - loss: 0.3714 - mse: 191.6176

45/45 [==============================] - 0s 7ms/step - loss: 0.3714 - mse: 191.6176 - val_loss: 0.4674 - val_mse: 188.1802
Epoch 26/30

 1/45 [..............................] - ETA: 0s - loss: 0.3377 - mse: 186.9965
14/45 [========>.....................] - ETA: 0s - loss: 0.3679 - mse: 189.6129
28/45 [=================>............] - ETA: 0s - loss: 0.3696 - mse: 190.7877
42/45 [===========================>..] - ETA: 0s - loss: 0.3675 - mse: 191.8069
45/45 [==============================] - 0s 4ms/step - loss: 0.3678 - mse: 191.6176

45/45 [==============================] - 0s 7ms/step - loss: 0.3678 - mse: 191.6176 - val_loss: 0.4536 - val_mse: 188.1803
Epoch 27/30

 1/45 [..............................] - ETA: 0s - loss: 0.4053 - mse: 212.7643
15/45 [=========>....................] - ETA: 0s - loss: 0.3934 - mse: 194.2865
29/45 [==================>...........] - ETA: 0s - loss: 0.3719 - mse: 191.0378
43/45 [===========================>..] - ETA: 0s - loss: 0.3614 - mse: 191.2429
45/45 [==============================] - 0s 4ms/step - loss: 0.3616 - mse: 191.6178

45/45 [==============================] - 0s 7ms/step - loss: 0.3616 - mse: 191.6178 - val_loss: 0.4629 - val_mse: 188.1803
Epoch 28/30

 1/45 [..............................] - ETA: 0s - loss: 0.3687 - mse: 205.7242
15/45 [=========>....................] - ETA: 0s - loss: 0.3504 - mse: 188.4982
29/45 [==================>...........] - ETA: 0s - loss: 0.3497 - mse: 188.4724
43/45 [===========================>..] - ETA: 0s - loss: 0.3456 - mse: 191.1547
45/45 [==============================] - 0s 4ms/step - loss: 0.3462 - mse: 191.6178

45/45 [==============================] - 0s 7ms/step - loss: 0.3462 - mse: 191.6178 - val_loss: 0.4721 - val_mse: 188.1805
Epoch 29/30

 1/45 [..............................] - ETA: 0s - loss: 0.3523 - mse: 186.0832
14/45 [========>.....................] - ETA: 0s - loss: 0.3468 - mse: 187.1259
28/45 [=================>............] - ETA: 0s - loss: 0.3423 - mse: 190.2278
42/45 [===========================>..] - ETA: 0s - loss: 0.3397 - mse: 191.9328
45/45 [==============================] - 0s 4ms/step - loss: 0.3384 - mse: 191.6179

45/45 [==============================] - 0s 7ms/step - loss: 0.3384 - mse: 191.6179 - val_loss: 0.4039 - val_mse: 188.1805
Epoch 30/30

 1/45 [..............................] - ETA: 0s - loss: 0.3367 - mse: 198.1452
14/45 [========>.....................] - ETA: 0s - loss: 0.3410 - mse: 190.5233
28/45 [=================>............] - ETA: 0s - loss: 0.3332 - mse: 189.9466
42/45 [===========================>..] - ETA: 0s - loss: 0.3272 - mse: 190.8776
45/45 [==============================] - 0s 4ms/step - loss: 0.3264 - mse: 191.6180

45/45 [==============================] - 0s 7ms/step - loss: 0.3264 - mse: 191.6180 - val_loss: 0.4591 - val_mse: 188.1806

Run completed: runs/2023-04-03T22-34-51Z

bike_runs

Data frame: 9 x 25 

# ... with 20 more columns:
#   flag_nodes, flag_batch_size, flag_activation, flag_learning_rate, flag_epochs, epochs, epochs_completed, metrics, model, loss_function, optimizer,
#   learning_rate, script, start, end, completed, output, source_code, context, type

Based on the runs, it appears that run number 3 had the best mean squared error on the validation data.

view_run(bike_runs$run_dir[3])

Warning: argument 'compressed' is ignored for the internal methodWarning: incomplete final line found on 'C:\Users\JERRYP~1\AppData\Local\Temp\Rtmpyotyha\file6af82ff82858/source/bike_tune.R'Warning: incomplete final line found on 'C:\Users\JERRYP~1\AppData\Local\Temp\Rtmpyotyha\file6af82ff82858/source/adult_hyperparams (1).R'Warning: incomplete final line found on 'C:\Users\JERRYP~1\AppData\Local\Temp\Rtmpyotyha\file6af82ff82858/source/Corona_NLP_train.R'Warning: incomplete final line found on 'C:\Users\JERRYP~1\AppData\Local\Temp\Rtmpyotyha\file6af82ff82858/source/fashion_mnist.R'

The best model seems to overfit slightly.

The validation_loss seems to roughly stop decreasing around 70 epochs.

12. Measure the performance of the best model on the test set and compute its RMSE.

bike_model = keras_model_sequential()

bike_model %>%
  layer_dense(units = 128, activation = "tanh", input_shape = 106)%>%
  layer_dense(units = 128, activation = "tanh",) %>%
  layer_dense(units = 106, activation = "softmax")


bike_model %>% compile(
  optimizer = optimizer_adam(lr = .001),
  loss = 'sparse_categorical_crossentropy',
  metrics = c('mse')
)

WARNING:absl:`lr` is deprecated, please use `learning_rate` instead, or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.

bike_model %>% fit(
  second_bikes_matrix, second_bikes_train_set$count, epochs = 100, batch_size = 200, validation_data = list(as.matrix(second_bikes_valid_matrix), second_bikes_valid$count)
)

Epoch 1/100

 1/45 [..............................] - ETA: 15s - loss: 4.8178 - mse: 213.2808
14/45 [========>.....................] - ETA: 0s - loss: 3.9802 - mse: 191.6415 
28/45 [=================>............] - ETA: 0s - loss: 3.5402 - mse: 190.1277
42/45 [===========================>..] - ETA: 0s - loss: 3.2796 - mse: 191.3943
45/45 [==============================] - 1s 4ms/step - loss: 3.2477 - mse: 191.6117

45/45 [==============================] - 1s 18ms/step - loss: 3.2477 - mse: 191.6117 - val_loss: 2.5804 - val_mse: 188.1748
Epoch 2/100

 1/45 [..............................] - ETA: 0s - loss: 2.4876 - mse: 173.4033
14/45 [========>.....................] - ETA: 0s - loss: 2.4813 - mse: 188.6700
27/45 [=================>............] - ETA: 0s - loss: 2.4132 - mse: 190.9499
41/45 [==========================>...] - ETA: 0s - loss: 2.3397 - mse: 191.4678
45/45 [==============================] - 0s 4ms/step - loss: 2.3262 - mse: 191.6122

45/45 [==============================] - 0s 7ms/step - loss: 2.3262 - mse: 191.6122 - val_loss: 2.1318 - val_mse: 188.1752
Epoch 3/100

 1/45 [..............................] - ETA: 0s - loss: 2.1696 - mse: 207.5636
15/45 [=========>....................] - ETA: 0s - loss: 2.0628 - mse: 193.6133
29/45 [==================>...........] - ETA: 0s - loss: 2.0033 - mse: 193.2639
43/45 [===========================>..] - ETA: 0s - loss: 1.9531 - mse: 191.8408
45/45 [==============================] - 0s 4ms/step - loss: 1.9477 - mse: 191.6126

45/45 [==============================] - 0s 7ms/step - loss: 1.9477 - mse: 191.6126 - val_loss: 1.8575 - val_mse: 188.1756
Epoch 4/100

 1/45 [..............................] - ETA: 0s - loss: 1.9218 - mse: 208.1331
15/45 [=========>....................] - ETA: 0s - loss: 1.7514 - mse: 187.0316
29/45 [==================>...........] - ETA: 0s - loss: 1.7244 - mse: 189.9549
43/45 [===========================>..] - ETA: 0s - loss: 1.6990 - mse: 192.1464
45/45 [==============================] - 0s 4ms/step - loss: 1.6945 - mse: 191.6128

45/45 [==============================] - 0s 7ms/step - loss: 1.6945 - mse: 191.6128 - val_loss: 1.6037 - val_mse: 188.1759
Epoch 5/100

 1/45 [..............................] - ETA: 0s - loss: 1.6389 - mse: 200.4010
15/45 [=========>....................] - ETA: 0s - loss: 1.5471 - mse: 191.1449
29/45 [==================>...........] - ETA: 0s - loss: 1.5230 - mse: 191.4918
43/45 [===========================>..] - ETA: 0s - loss: 1.4957 - mse: 191.7388
45/45 [==============================] - 0s 4ms/step - loss: 1.4943 - mse: 191.6132

45/45 [==============================] - 0s 7ms/step - loss: 1.4943 - mse: 191.6132 - val_loss: 1.4313 - val_mse: 188.1762
Epoch 6/100

 1/45 [..............................] - ETA: 0s - loss: 1.3739 - mse: 188.0342
15/45 [=========>....................] - ETA: 0s - loss: 1.3981 - mse: 195.5275
29/45 [==================>...........] - ETA: 0s - loss: 1.3573 - mse: 191.4886
43/45 [===========================>..] - ETA: 0s - loss: 1.3363 - mse: 190.7672
45/45 [==============================] - 0s 4ms/step - loss: 1.3370 - mse: 191.6136

45/45 [==============================] - 0s 7ms/step - loss: 1.3370 - mse: 191.6136 - val_loss: 1.2838 - val_mse: 188.1765
Epoch 7/100

 1/45 [..............................] - ETA: 0s - loss: 1.2199 - mse: 178.4163
15/45 [=========>....................] - ETA: 0s - loss: 1.2463 - mse: 191.2640
29/45 [==================>...........] - ETA: 0s - loss: 1.2228 - mse: 192.4206
43/45 [===========================>..] - ETA: 0s - loss: 1.2023 - mse: 191.5864
45/45 [==============================] - 0s 4ms/step - loss: 1.2008 - mse: 191.6138

45/45 [==============================] - 0s 7ms/step - loss: 1.2008 - mse: 191.6138 - val_loss: 1.1546 - val_mse: 188.1767
Epoch 8/100

 1/45 [..............................] - ETA: 0s - loss: 1.1380 - mse: 193.7921
15/45 [=========>....................] - ETA: 0s - loss: 1.1182 - mse: 190.0037
29/45 [==================>...........] - ETA: 0s - loss: 1.1071 - mse: 192.1561
43/45 [===========================>..] - ETA: 0s - loss: 1.0871 - mse: 191.6347
45/45 [==============================] - 0s 4ms/step - loss: 1.0862 - mse: 191.6142

45/45 [==============================] - 0s 8ms/step - loss: 1.0862 - mse: 191.6142 - val_loss: 1.0473 - val_mse: 188.1770
Epoch 9/100

 1/45 [..............................] - ETA: 0s - loss: 1.0438 - mse: 203.9482
14/45 [========>.....................] - ETA: 0s - loss: 1.0284 - mse: 195.5623
28/45 [=================>............] - ETA: 0s - loss: 1.0112 - mse: 194.2076
42/45 [===========================>..] - ETA: 0s - loss: 0.9925 - mse: 192.1043
45/45 [==============================] - 0s 4ms/step - loss: 0.9898 - mse: 191.6144

45/45 [==============================] - 0s 7ms/step - loss: 0.9898 - mse: 191.6144 - val_loss: 0.9672 - val_mse: 188.1774
Epoch 10/100

 1/45 [..............................] - ETA: 0s - loss: 0.9606 - mse: 198.9178
15/45 [=========>....................] - ETA: 0s - loss: 0.9528 - mse: 196.1711
29/45 [==================>...........] - ETA: 0s - loss: 0.9309 - mse: 193.9189
43/45 [===========================>..] - ETA: 0s - loss: 0.9084 - mse: 191.8271
45/45 [==============================] - 0s 4ms/step - loss: 0.9067 - mse: 191.6147

45/45 [==============================] - 0s 7ms/step - loss: 0.9067 - mse: 191.6147 - val_loss: 0.8976 - val_mse: 188.1776
Epoch 11/100

 1/45 [..............................] - ETA: 0s - loss: 0.8743 - mse: 204.1037
15/45 [=========>....................] - ETA: 0s - loss: 0.8757 - mse: 198.2641
29/45 [==================>...........] - ETA: 0s - loss: 0.8630 - mse: 196.0952
43/45 [===========================>..] - ETA: 0s - loss: 0.8393 - mse: 191.3338
45/45 [==============================] - 0s 4ms/step - loss: 0.8401 - mse: 191.6150

45/45 [==============================] - 0s 7ms/step - loss: 0.8401 - mse: 191.6150 - val_loss: 0.8370 - val_mse: 188.1779
Epoch 12/100

 1/45 [..............................] - ETA: 0s - loss: 0.7888 - mse: 187.2608
14/45 [========>.....................] - ETA: 0s - loss: 0.8045 - mse: 192.6724
27/45 [=================>............] - ETA: 0s - loss: 0.7940 - mse: 193.1661
40/45 [=========================>....] - ETA: 0s - loss: 0.7801 - mse: 191.1619
45/45 [==============================] - 0s 4ms/step - loss: 0.7797 - mse: 191.6152

45/45 [==============================] - 0s 7ms/step - loss: 0.7797 - mse: 191.6152 - val_loss: 0.7845 - val_mse: 188.1781
Epoch 13/100

 1/45 [..............................] - ETA: 0s - loss: 0.7610 - mse: 204.9231
15/45 [=========>....................] - ETA: 0s - loss: 0.7540 - mse: 197.2404
29/45 [==================>...........] - ETA: 0s - loss: 0.7367 - mse: 193.2917
43/45 [===========================>..] - ETA: 0s - loss: 0.7278 - mse: 192.1947
45/45 [==============================] - 0s 4ms/step - loss: 0.7263 - mse: 191.6155

45/45 [==============================] - 0s 7ms/step - loss: 0.7263 - mse: 191.6155 - val_loss: 0.7449 - val_mse: 188.1783
Epoch 14/100

 1/45 [..............................] - ETA: 0s - loss: 0.7317 - mse: 198.8666
14/45 [========>.....................] - ETA: 0s - loss: 0.6923 - mse: 190.7620
27/45 [=================>............] - ETA: 0s - loss: 0.6853 - mse: 190.6098
40/45 [=========================>....] - ETA: 0s - loss: 0.6820 - mse: 191.7609
45/45 [==============================] - 0s 4ms/step - loss: 0.6779 - mse: 191.6157

45/45 [==============================] - 0s 7ms/step - loss: 0.6779 - mse: 191.6157 - val_loss: 0.7061 - val_mse: 188.1786
Epoch 15/100

 1/45 [..............................] - ETA: 0s - loss: 0.5743 - mse: 158.1160
 9/45 [=====>........................] - ETA: 0s - loss: 0.6581 - mse: 191.3233
21/45 [=============>................] - ETA: 0s - loss: 0.6485 - mse: 190.6107
34/45 [=====================>........] - ETA: 0s - loss: 0.6422 - mse: 191.0294
45/45 [==============================] - 0s 4ms/step - loss: 0.6383 - mse: 191.6159

45/45 [==============================] - 0s 8ms/step - loss: 0.6383 - mse: 191.6159 - val_loss: 0.6521 - val_mse: 188.1788
Epoch 16/100

 1/45 [..............................] - ETA: 0s - loss: 0.5899 - mse: 177.3487
14/45 [========>.....................] - ETA: 0s - loss: 0.6207 - mse: 196.2731
28/45 [=================>............] - ETA: 0s - loss: 0.6120 - mse: 193.5213
42/45 [===========================>..] - ETA: 0s - loss: 0.5969 - mse: 191.8266
45/45 [==============================] - 0s 4ms/step - loss: 0.5958 - mse: 191.6161

45/45 [==============================] - 0s 7ms/step - loss: 0.5958 - mse: 191.6161 - val_loss: 0.6144 - val_mse: 188.1790
Epoch 17/100

 1/45 [..............................] - ETA: 0s - loss: 0.4788 - mse: 164.9710
15/45 [=========>....................] - ETA: 0s - loss: 0.5670 - mse: 190.7419
28/45 [=================>............] - ETA: 0s - loss: 0.5705 - mse: 192.5876
41/45 [==========================>...] - ETA: 0s - loss: 0.5643 - mse: 191.7355
45/45 [==============================] - 0s 4ms/step - loss: 0.5633 - mse: 191.6164

45/45 [==============================] - 0s 7ms/step - loss: 0.5633 - mse: 191.6164 - val_loss: 0.5923 - val_mse: 188.1792
Epoch 18/100

 1/45 [..............................] - ETA: 0s - loss: 0.5188 - mse: 193.3138
14/45 [========>.....................] - ETA: 0s - loss: 0.5528 - mse: 196.8569
27/45 [=================>............] - ETA: 0s - loss: 0.5474 - mse: 195.2786
41/45 [==========================>...] - ETA: 0s - loss: 0.5340 - mse: 191.7784
45/45 [==============================] - 0s 4ms/step - loss: 0.5341 - mse: 191.6165

45/45 [==============================] - 0s 7ms/step - loss: 0.5341 - mse: 191.6165 - val_loss: 0.6117 - val_mse: 188.1793
Epoch 19/100

 1/45 [..............................] - ETA: 0s - loss: 0.4822 - mse: 168.9058
14/45 [========>.....................] - ETA: 0s - loss: 0.5194 - mse: 192.6536
28/45 [=================>............] - ETA: 0s - loss: 0.5113 - mse: 190.9590
42/45 [===========================>..] - ETA: 0s - loss: 0.5081 - mse: 192.1803
45/45 [==============================] - 0s 4ms/step - loss: 0.5065 - mse: 191.6167

45/45 [==============================] - 0s 7ms/step - loss: 0.5065 - mse: 191.6167 - val_loss: 0.5272 - val_mse: 188.1795
Epoch 20/100

 1/45 [..............................] - ETA: 0s - loss: 0.5037 - mse: 184.6682
14/45 [========>.....................] - ETA: 0s - loss: 0.5002 - mse: 191.8711
28/45 [=================>............] - ETA: 0s - loss: 0.4856 - mse: 190.3622
42/45 [===========================>..] - ETA: 0s - loss: 0.4844 - mse: 191.5929
45/45 [==============================] - 0s 4ms/step - loss: 0.4841 - mse: 191.6169

45/45 [==============================] - 0s 7ms/step - loss: 0.4841 - mse: 191.6169 - val_loss: 0.5400 - val_mse: 188.1796
Epoch 21/100

 1/45 [..............................] - ETA: 0s - loss: 0.5007 - mse: 209.2066
15/45 [=========>....................] - ETA: 0s - loss: 0.4716 - mse: 194.6300
28/45 [=================>............] - ETA: 0s - loss: 0.4627 - mse: 192.7932
42/45 [===========================>..] - ETA: 0s - loss: 0.4590 - mse: 192.1055
45/45 [==============================] - 0s 4ms/step - loss: 0.4578 - mse: 191.6170

45/45 [==============================] - 0s 7ms/step - loss: 0.4578 - mse: 191.6170 - val_loss: 0.4758 - val_mse: 188.1798
Epoch 22/100

 1/45 [..............................] - ETA: 0s - loss: 0.4994 - mse: 199.9755
15/45 [=========>....................] - ETA: 0s - loss: 0.4783 - mse: 196.8005
29/45 [==================>...........] - ETA: 0s - loss: 0.4549 - mse: 190.7830
43/45 [===========================>..] - ETA: 0s - loss: 0.4477 - mse: 191.8280
45/45 [==============================] - 0s 4ms/step - loss: 0.4469 - mse: 191.6171

45/45 [==============================] - 0s 7ms/step - loss: 0.4469 - mse: 191.6171 - val_loss: 0.4967 - val_mse: 188.1799
Epoch 23/100

 1/45 [..............................] - ETA: 0s - loss: 0.3896 - mse: 179.0330
14/45 [========>.....................] - ETA: 0s - loss: 0.4151 - mse: 193.2533
28/45 [=================>............] - ETA: 0s - loss: 0.4175 - mse: 191.9261
42/45 [===========================>..] - ETA: 0s - loss: 0.4122 - mse: 191.3481
45/45 [==============================] - 0s 4ms/step - loss: 0.4123 - mse: 191.6173

45/45 [==============================] - 0s 7ms/step - loss: 0.4123 - mse: 191.6173 - val_loss: 0.4644 - val_mse: 188.1800
Epoch 24/100

 1/45 [..............................] - ETA: 0s - loss: 0.4029 - mse: 194.5659
14/45 [========>.....................] - ETA: 0s - loss: 0.3906 - mse: 187.0507
27/45 [=================>............] - ETA: 0s - loss: 0.3896 - mse: 188.5636
40/45 [=========================>....] - ETA: 0s - loss: 0.3930 - mse: 191.2791
45/45 [==============================] - 0s 4ms/step - loss: 0.3936 - mse: 191.6174

45/45 [==============================] - 0s 7ms/step - loss: 0.3936 - mse: 191.6174 - val_loss: 0.4671 - val_mse: 188.1801
Epoch 25/100

 1/45 [..............................] - ETA: 0s - loss: 0.4529 - mse: 223.6005
15/45 [=========>....................] - ETA: 0s - loss: 0.3905 - mse: 193.4578
28/45 [=================>............] - ETA: 0s - loss: 0.3855 - mse: 191.0284
42/45 [===========================>..] - ETA: 0s - loss: 0.3821 - mse: 191.4896
45/45 [==============================] - 0s 4ms/step - loss: 0.3821 - mse: 191.6176

45/45 [==============================] - 0s 7ms/step - loss: 0.3821 - mse: 191.6176 - val_loss: 0.4075 - val_mse: 188.1802
Epoch 26/100

 1/45 [..............................] - ETA: 0s - loss: 0.3845 - mse: 197.9300
14/45 [========>.....................] - ETA: 0s - loss: 0.3742 - mse: 190.5157
27/45 [=================>............] - ETA: 0s - loss: 0.3746 - mse: 192.2138
40/45 [=========================>....] - ETA: 0s - loss: 0.3696 - mse: 191.7647
45/45 [==============================] - 0s 4ms/step - loss: 0.3695 - mse: 191.6176

45/45 [==============================] - 0s 7ms/step - loss: 0.3695 - mse: 191.6176 - val_loss: 0.4117 - val_mse: 188.1803
Epoch 27/100

 1/45 [..............................] - ETA: 0s - loss: 0.3798 - mse: 208.2565
15/45 [=========>....................] - ETA: 0s - loss: 0.3651 - mse: 192.4194
29/45 [==================>...........] - ETA: 0s - loss: 0.3600 - mse: 192.8920
42/45 [===========================>..] - ETA: 0s - loss: 0.3504 - mse: 191.6551
45/45 [==============================] - 0s 4ms/step - loss: 0.3495 - mse: 191.6178

45/45 [==============================] - 0s 7ms/step - loss: 0.3495 - mse: 191.6178 - val_loss: 0.4639 - val_mse: 188.1805
Epoch 28/100

 1/45 [..............................] - ETA: 0s - loss: 0.3519 - mse: 197.7042
14/45 [========>.....................] - ETA: 0s - loss: 0.3414 - mse: 190.4713
28/45 [=================>............] - ETA: 0s - loss: 0.3451 - mse: 192.4616
42/45 [===========================>..] - ETA: 0s - loss: 0.3372 - mse: 190.5425
45/45 [==============================] - 0s 4ms/step - loss: 0.3389 - mse: 191.6178

45/45 [==============================] - 0s 7ms/step - loss: 0.3389 - mse: 191.6178 - val_loss: 0.4125 - val_mse: 188.1806
Epoch 29/100

 1/45 [..............................] - ETA: 0s - loss: 0.3052 - mse: 180.9220
15/45 [=========>....................] - ETA: 0s - loss: 0.3237 - mse: 192.7763
29/45 [==================>...........] - ETA: 0s - loss: 0.3207 - mse: 190.9790
43/45 [===========================>..] - ETA: 0s - loss: 0.3234 - mse: 191.8812
45/45 [==============================] - 0s 4ms/step - loss: 0.3235 - mse: 191.6179

45/45 [==============================] - 0s 7ms/step - loss: 0.3235 - mse: 191.6179 - val_loss: 0.4148 - val_mse: 188.1806
Epoch 30/100

 1/45 [..............................] - ETA: 0s - loss: 0.3063 - mse: 190.1983
15/45 [=========>....................] - ETA: 0s - loss: 0.3129 - mse: 192.6886
28/45 [=================>............] - ETA: 0s - loss: 0.3101 - mse: 189.6942
42/45 [===========================>..] - ETA: 0s - loss: 0.3134 - mse: 191.9335
45/45 [==============================] - 0s 4ms/step - loss: 0.3131 - mse: 191.6180

45/45 [==============================] - 0s 7ms/step - loss: 0.3131 - mse: 191.6180 - val_loss: 0.3597 - val_mse: 188.1807
Epoch 31/100

 1/45 [..............................] - ETA: 0s - loss: 0.2755 - mse: 184.8492
15/45 [=========>....................] - ETA: 0s - loss: 0.3059 - mse: 190.0919
29/45 [==================>...........] - ETA: 0s - loss: 0.3070 - mse: 190.9821
42/45 [===========================>..] - ETA: 0s - loss: 0.3039 - mse: 191.4221
45/45 [==============================] - 0s 4ms/step - loss: 0.3038 - mse: 191.6181

45/45 [==============================] - 0s 7ms/step - loss: 0.3038 - mse: 191.6181 - val_loss: 0.3643 - val_mse: 188.1808
Epoch 32/100

 1/45 [..............................] - ETA: 0s - loss: 0.2973 - mse: 196.9322
14/45 [========>.....................] - ETA: 0s - loss: 0.3003 - mse: 189.5349
28/45 [=================>............] - ETA: 0s - loss: 0.3006 - mse: 191.7490
42/45 [===========================>..] - ETA: 0s - loss: 0.2946 - mse: 191.6326
45/45 [==============================] - 0s 4ms/step - loss: 0.2934 - mse: 191.6181

45/45 [==============================] - 0s 7ms/step - loss: 0.2934 - mse: 191.6181 - val_loss: 0.4492 - val_mse: 188.1808
Epoch 33/100

 1/45 [..............................] - ETA: 0s - loss: 0.3233 - mse: 195.7352
14/45 [========>.....................] - ETA: 0s - loss: 0.2928 - mse: 192.1369
27/45 [=================>............] - ETA: 0s - loss: 0.2866 - mse: 192.5943
40/45 [=========================>....] - ETA: 0s - loss: 0.2821 - mse: 192.1832
45/45 [==============================] - 0s 4ms/step - loss: 0.2806 - mse: 191.6183

45/45 [==============================] - 0s 7ms/step - loss: 0.2806 - mse: 191.6183 - val_loss: 0.3468 - val_mse: 188.1809
Epoch 34/100

 1/45 [..............................] - ETA: 0s - loss: 0.2413 - mse: 180.4107
14/45 [========>.....................] - ETA: 0s - loss: 0.2724 - mse: 192.2659
28/45 [=================>............] - ETA: 0s - loss: 0.2744 - mse: 192.7010
41/45 [==========================>...] - ETA: 0s - loss: 0.2725 - mse: 191.9252
45/45 [==============================] - 0s 4ms/step - loss: 0.2703 - mse: 191.6183

45/45 [==============================] - 0s 7ms/step - loss: 0.2703 - mse: 191.6183 - val_loss: 0.3262 - val_mse: 188.1810
Epoch 35/100

 1/45 [..............................] - ETA: 0s - loss: 0.2103 - mse: 174.9117
14/45 [========>.....................] - ETA: 0s - loss: 0.2610 - mse: 191.3334
27/45 [=================>............] - ETA: 0s - loss: 0.2614 - mse: 191.8463
41/45 [==========================>...] - ETA: 0s - loss: 0.2581 - mse: 191.1569
45/45 [==============================] - 0s 4ms/step - loss: 0.2604 - mse: 191.6184

45/45 [==============================] - 0s 7ms/step - loss: 0.2604 - mse: 191.6184 - val_loss: 0.3538 - val_mse: 188.1811
Epoch 36/100

 1/45 [..............................] - ETA: 0s - loss: 0.2757 - mse: 205.5373
14/45 [========>.....................] - ETA: 0s - loss: 0.2610 - mse: 195.7785
27/45 [=================>............] - ETA: 0s - loss: 0.2549 - mse: 193.4193
40/45 [=========================>....] - ETA: 0s - loss: 0.2533 - mse: 191.5967
45/45 [==============================] - 0s 4ms/step - loss: 0.2532 - mse: 191.6185

45/45 [==============================] - 0s 8ms/step - loss: 0.2532 - mse: 191.6185 - val_loss: 0.3505 - val_mse: 188.1811
Epoch 37/100

 1/45 [..............................] - ETA: 0s - loss: 0.2360 - mse: 186.4926
14/45 [========>.....................] - ETA: 0s - loss: 0.2446 - mse: 193.0757
27/45 [=================>............] - ETA: 0s - loss: 0.2455 - mse: 192.5169
41/45 [==========================>...] - ETA: 0s - loss: 0.2414 - mse: 191.2533
45/45 [==============================] - 0s 4ms/step - loss: 0.2426 - mse: 191.6185

45/45 [==============================] - 0s 7ms/step - loss: 0.2426 - mse: 191.6185 - val_loss: 0.3498 - val_mse: 188.1812
Epoch 38/100

 1/45 [..............................] - ETA: 0s - loss: 0.2780 - mse: 209.7536
14/45 [========>.....................] - ETA: 0s - loss: 0.2494 - mse: 195.8544
28/45 [=================>............] - ETA: 0s - loss: 0.2351 - mse: 189.5598
41/45 [==========================>...] - ETA: 0s - loss: 0.2358 - mse: 190.3797
45/45 [==============================] - 0s 4ms/step - loss: 0.2373 - mse: 191.6186

45/45 [==============================] - 0s 7ms/step - loss: 0.2373 - mse: 191.6186 - val_loss: 0.3447 - val_mse: 188.1813
Epoch 39/100

 1/45 [..............................] - ETA: 0s - loss: 0.2458 - mse: 198.7869
14/45 [========>.....................] - ETA: 0s - loss: 0.2442 - mse: 197.0582
27/45 [=================>............] - ETA: 0s - loss: 0.2368 - mse: 192.7402
40/45 [=========================>....] - ETA: 0s - loss: 0.2366 - mse: 192.3282
45/45 [==============================] - 0s 4ms/step - loss: 0.2342 - mse: 191.6187

45/45 [==============================] - 0s 7ms/step - loss: 0.2342 - mse: 191.6187 - val_loss: 0.3325 - val_mse: 188.1813
Epoch 40/100

 1/45 [..............................] - ETA: 0s - loss: 0.2312 - mse: 183.2591
13/45 [=======>......................] - ETA: 0s - loss: 0.2286 - mse: 190.9063
26/45 [================>.............] - ETA: 0s - loss: 0.2263 - mse: 192.5414
39/45 [=========================>....] - ETA: 0s - loss: 0.2279 - mse: 192.8093
45/45 [==============================] - 0s 4ms/step - loss: 0.2268 - mse: 191.6187

45/45 [==============================] - 0s 7ms/step - loss: 0.2268 - mse: 191.6187 - val_loss: 0.4118 - val_mse: 188.1813
Epoch 41/100

 1/45 [..............................] - ETA: 0s - loss: 0.1907 - mse: 176.2865
14/45 [========>.....................] - ETA: 0s - loss: 0.2189 - mse: 185.0556
27/45 [=================>............] - ETA: 0s - loss: 0.2201 - mse: 189.1037
40/45 [=========================>....] - ETA: 0s - loss: 0.2207 - mse: 191.7097
45/45 [==============================] - 0s 4ms/step - loss: 0.2203 - mse: 191.6188

45/45 [==============================] - 0s 8ms/step - loss: 0.2203 - mse: 191.6188 - val_loss: 0.3385 - val_mse: 188.1813
Epoch 42/100

 1/45 [..............................] - ETA: 0s - loss: 0.2056 - mse: 207.0840
14/45 [========>.....................] - ETA: 0s - loss: 0.2357 - mse: 189.9960
27/45 [=================>............] - ETA: 0s - loss: 0.2336 - mse: 191.1532
40/45 [=========================>....] - ETA: 0s - loss: 0.2271 - mse: 190.3403
45/45 [==============================] - 0s 4ms/step - loss: 0.2285 - mse: 191.6187

45/45 [==============================] - 0s 8ms/step - loss: 0.2285 - mse: 191.6187 - val_loss: 0.3246 - val_mse: 188.1814
Epoch 43/100

 1/45 [..............................] - ETA: 0s - loss: 0.2012 - mse: 180.6557
14/45 [========>.....................] - ETA: 0s - loss: 0.1953 - mse: 185.5512
27/45 [=================>............] - ETA: 0s - loss: 0.2023 - mse: 189.5063
41/45 [==========================>...] - ETA: 0s - loss: 0.2053 - mse: 191.1163
45/45 [==============================] - 0s 4ms/step - loss: 0.2069 - mse: 191.6189

45/45 [==============================] - 0s 7ms/step - loss: 0.2069 - mse: 191.6189 - val_loss: 0.3354 - val_mse: 188.1814
Epoch 44/100

 1/45 [..............................] - ETA: 0s - loss: 0.1949 - mse: 182.1441
15/45 [=========>....................] - ETA: 0s - loss: 0.2074 - mse: 189.6212
28/45 [=================>............] - ETA: 0s - loss: 0.2035 - mse: 191.7463
41/45 [==========================>...] - ETA: 0s - loss: 0.2004 - mse: 191.2626
45/45 [==============================] - 0s 4ms/step - loss: 0.2017 - mse: 191.6189

45/45 [==============================] - 0s 7ms/step - loss: 0.2017 - mse: 191.6189 - val_loss: 0.2937 - val_mse: 188.1815
Epoch 45/100

 1/45 [..............................] - ETA: 0s - loss: 0.1959 - mse: 182.9184
14/45 [========>.....................] - ETA: 0s - loss: 0.1918 - mse: 186.9460
27/45 [=================>............] - ETA: 0s - loss: 0.1938 - mse: 190.4140
40/45 [=========================>....] - ETA: 0s - loss: 0.1947 - mse: 191.1749
45/45 [==============================] - 0s 4ms/step - loss: 0.1955 - mse: 191.6189

45/45 [==============================] - 0s 7ms/step - loss: 0.1955 - mse: 191.6189 - val_loss: 0.3027 - val_mse: 188.1815
Epoch 46/100

 1/45 [..............................] - ETA: 0s - loss: 0.2290 - mse: 222.0513
14/45 [========>.....................] - ETA: 0s - loss: 0.1907 - mse: 191.6534
28/45 [=================>............] - ETA: 0s - loss: 0.1916 - mse: 191.3683
41/45 [==========================>...] - ETA: 0s - loss: 0.1909 - mse: 191.3163
45/45 [==============================] - 0s 4ms/step - loss: 0.1912 - mse: 191.6190

45/45 [==============================] - 0s 7ms/step - loss: 0.1912 - mse: 191.6190 - val_loss: 0.3639 - val_mse: 188.1816
Epoch 47/100

 1/45 [..............................] - ETA: 0s - loss: 0.2228 - mse: 200.9978
14/45 [========>.....................] - ETA: 0s - loss: 0.1895 - mse: 190.8603
27/45 [=================>............] - ETA: 0s - loss: 0.1880 - mse: 190.9636
41/45 [==========================>...] - ETA: 0s - loss: 0.1864 - mse: 191.9001
45/45 [==============================] - 0s 4ms/step - loss: 0.1854 - mse: 191.6190

45/45 [==============================] - 0s 7ms/step - loss: 0.1854 - mse: 191.6190 - val_loss: 0.3120 - val_mse: 188.1816
Epoch 48/100

 1/45 [..............................] - ETA: 0s - loss: 0.1794 - mse: 192.0677
14/45 [========>.....................] - ETA: 0s - loss: 0.1954 - mse: 194.5641
27/45 [=================>............] - ETA: 0s - loss: 0.1916 - mse: 194.9899
40/45 [=========================>....] - ETA: 0s - loss: 0.1857 - mse: 192.2714
45/45 [==============================] - 0s 4ms/step - loss: 0.1840 - mse: 191.6191

45/45 [==============================] - 0s 7ms/step - loss: 0.1840 - mse: 191.6191 - val_loss: 0.2823 - val_mse: 188.1816
Epoch 49/100

 1/45 [..............................] - ETA: 0s - loss: 0.1793 - mse: 200.7028
14/45 [========>.....................] - ETA: 0s - loss: 0.1799 - mse: 188.9444
27/45 [=================>............] - ETA: 0s - loss: 0.1840 - mse: 190.9666
40/45 [=========================>....] - ETA: 0s - loss: 0.1842 - mse: 191.2377
45/45 [==============================] - 0s 4ms/step - loss: 0.1840 - mse: 191.6191

45/45 [==============================] - 0s 7ms/step - loss: 0.1840 - mse: 191.6191 - val_loss: 0.2875 - val_mse: 188.1816
Epoch 50/100

 1/45 [..............................] - ETA: 0s - loss: 0.1588 - mse: 186.5354
15/45 [=========>....................] - ETA: 0s - loss: 0.1732 - mse: 192.3130
28/45 [=================>............] - ETA: 0s - loss: 0.1724 - mse: 190.3056
42/45 [===========================>..] - ETA: 0s - loss: 0.1727 - mse: 192.2194
45/45 [==============================] - 0s 4ms/step - loss: 0.1714 - mse: 191.6191

45/45 [==============================] - 0s 7ms/step - loss: 0.1714 - mse: 191.6191 - val_loss: 0.2541 - val_mse: 188.1817
Epoch 51/100

 1/45 [..............................] - ETA: 0s - loss: 0.1711 - mse: 189.4787
14/45 [========>.....................] - ETA: 0s - loss: 0.1818 - mse: 190.9321
27/45 [=================>............] - ETA: 0s - loss: 0.1827 - mse: 192.6775
40/45 [=========================>....] - ETA: 0s - loss: 0.1748 - mse: 190.7030
45/45 [==============================] - 0s 4ms/step - loss: 0.1762 - mse: 191.6192

45/45 [==============================] - 0s 7ms/step - loss: 0.1762 - mse: 191.6192 - val_loss: 0.2884 - val_mse: 188.1818
Epoch 52/100

 1/45 [..............................] - ETA: 0s - loss: 0.1836 - mse: 196.0636
14/45 [========>.....................] - ETA: 0s - loss: 0.1638 - mse: 192.0324
27/45 [=================>............] - ETA: 0s - loss: 0.1635 - mse: 189.9689
40/45 [=========================>....] - ETA: 0s - loss: 0.1636 - mse: 191.2846
45/45 [==============================] - 0s 4ms/step - loss: 0.1640 - mse: 191.6192

45/45 [==============================] - 0s 7ms/step - loss: 0.1640 - mse: 191.6192 - val_loss: 0.2842 - val_mse: 188.1818
Epoch 53/100

 1/45 [..............................] - ETA: 0s - loss: 0.1242 - mse: 169.6218
15/45 [=========>....................] - ETA: 0s - loss: 0.1559 - mse: 189.7348
28/45 [=================>............] - ETA: 0s - loss: 0.1564 - mse: 190.9242
42/45 [===========================>..] - ETA: 0s - loss: 0.1554 - mse: 191.3324
45/45 [==============================] - 0s 4ms/step - loss: 0.1557 - mse: 191.6192

45/45 [==============================] - 0s 7ms/step - loss: 0.1557 - mse: 191.6192 - val_loss: 0.3262 - val_mse: 188.1818
Epoch 54/100

 1/45 [..............................] - ETA: 0s - loss: 0.1737 - mse: 218.9229
11/45 [======>.......................] - ETA: 0s - loss: 0.1506 - mse: 192.3369
22/45 [=============>................] - ETA: 0s - loss: 0.1543 - mse: 192.9239
33/45 [=====================>........] - ETA: 0s - loss: 0.1546 - mse: 192.2169
45/45 [==============================] - 0s 5ms/step - loss: 0.1564 - mse: 191.6193

45/45 [==============================] - 0s 8ms/step - loss: 0.1564 - mse: 191.6193 - val_loss: 0.3083 - val_mse: 188.1818
Epoch 55/100

 1/45 [..............................] - ETA: 0s - loss: 0.1113 - mse: 161.9375
15/45 [=========>....................] - ETA: 0s - loss: 0.1538 - mse: 189.5398
28/45 [=================>............] - ETA: 0s - loss: 0.1550 - mse: 191.6521
41/45 [==========================>...] - ETA: 0s - loss: 0.1564 - mse: 192.0651
45/45 [==============================] - 0s 4ms/step - loss: 0.1563 - mse: 191.6193

45/45 [==============================] - 0s 7ms/step - loss: 0.1563 - mse: 191.6193 - val_loss: 0.2583 - val_mse: 188.1819
Epoch 56/100

 1/45 [..............................] - ETA: 0s - loss: 0.1373 - mse: 172.5901
14/45 [========>.....................] - ETA: 0s - loss: 0.1515 - mse: 190.8064
27/45 [=================>............] - ETA: 0s - loss: 0.1489 - mse: 190.6751
40/45 [=========================>....] - ETA: 0s - loss: 0.1473 - mse: 190.6810
45/45 [==============================] - 0s 4ms/step - loss: 0.1490 - mse: 191.6193

45/45 [==============================] - 0s 7ms/step - loss: 0.1490 - mse: 191.6193 - val_loss: 0.2700 - val_mse: 188.1819
Epoch 57/100

 1/45 [..............................] - ETA: 0s - loss: 0.1162 - mse: 173.5874
14/45 [========>.....................] - ETA: 0s - loss: 0.1375 - mse: 186.4665
27/45 [=================>............] - ETA: 0s - loss: 0.1421 - mse: 190.0242
41/45 [==========================>...] - ETA: 0s - loss: 0.1443 - mse: 191.2976
45/45 [==============================] - 0s 4ms/step - loss: 0.1450 - mse: 191.6194

45/45 [==============================] - 0s 7ms/step - loss: 0.1450 - mse: 191.6194 - val_loss: 0.2529 - val_mse: 188.1820
Epoch 58/100

 1/45 [..............................] - ETA: 0s - loss: 0.1532 - mse: 207.9140
14/45 [========>.....................] - ETA: 0s - loss: 0.1434 - mse: 193.7101
27/45 [=================>............] - ETA: 0s - loss: 0.1416 - mse: 190.6334
40/45 [=========================>....] - ETA: 0s - loss: 0.1419 - mse: 191.6545
45/45 [==============================] - 0s 4ms/step - loss: 0.1420 - mse: 191.6194

45/45 [==============================] - 0s 7ms/step - loss: 0.1420 - mse: 191.6194 - val_loss: 0.2937 - val_mse: 188.1819
Epoch 59/100

 1/45 [..............................] - ETA: 0s - loss: 0.1235 - mse: 184.0952
14/45 [========>.....................] - ETA: 0s - loss: 0.1396 - mse: 187.6255
28/45 [=================>............] - ETA: 0s - loss: 0.1407 - mse: 189.9477
41/45 [==========================>...] - ETA: 0s - loss: 0.1424 - mse: 191.1160
45/45 [==============================] - 0s 4ms/step - loss: 0.1424 - mse: 191.6194

45/45 [==============================] - 0s 7ms/step - loss: 0.1424 - mse: 191.6194 - val_loss: 0.3366 - val_mse: 188.1819
Epoch 60/100

 1/45 [..............................] - ETA: 0s - loss: 0.1625 - mse: 202.8449
15/45 [=========>....................] - ETA: 0s - loss: 0.1552 - mse: 191.8981
29/45 [==================>...........] - ETA: 0s - loss: 0.1512 - mse: 191.1870
42/45 [===========================>..] - ETA: 0s - loss: 0.1473 - mse: 191.2762
45/45 [==============================] - 0s 4ms/step - loss: 0.1476 - mse: 191.6194

45/45 [==============================] - 0s 7ms/step - loss: 0.1476 - mse: 191.6194 - val_loss: 0.2621 - val_mse: 188.1820
Epoch 61/100

 1/45 [..............................] - ETA: 0s - loss: 0.1466 - mse: 189.9213
15/45 [=========>....................] - ETA: 0s - loss: 0.1374 - mse: 192.3176
28/45 [=================>............] - ETA: 0s - loss: 0.1309 - mse: 190.1059
41/45 [==========================>...] - ETA: 0s - loss: 0.1331 - mse: 191.2205
45/45 [==============================] - 0s 4ms/step - loss: 0.1336 - mse: 191.6195

45/45 [==============================] - 0s 7ms/step - loss: 0.1336 - mse: 191.6195 - val_loss: 0.3254 - val_mse: 188.1819
Epoch 62/100

 1/45 [..............................] - ETA: 0s - loss: 0.1236 - mse: 209.5406
14/45 [========>.....................] - ETA: 0s - loss: 0.1335 - mse: 193.0390
28/45 [=================>............] - ETA: 0s - loss: 0.1359 - mse: 191.9482
42/45 [===========================>..] - ETA: 0s - loss: 0.1357 - mse: 191.9384
45/45 [==============================] - 0s 4ms/step - loss: 0.1344 - mse: 191.6195

45/45 [==============================] - 0s 7ms/step - loss: 0.1344 - mse: 191.6195 - val_loss: 0.2906 - val_mse: 188.1820
Epoch 63/100

 1/45 [..............................] - ETA: 0s - loss: 0.1348 - mse: 213.2576
14/45 [========>.....................] - ETA: 0s - loss: 0.1481 - mse: 199.3161
27/45 [=================>............] - ETA: 0s - loss: 0.1370 - mse: 195.3915
41/45 [==========================>...] - ETA: 0s - loss: 0.1306 - mse: 192.2582
45/45 [==============================] - 0s 4ms/step - loss: 0.1307 - mse: 191.6195

45/45 [==============================] - 0s 7ms/step - loss: 0.1307 - mse: 191.6195 - val_loss: 0.2866 - val_mse: 188.1820
Epoch 64/100

 1/45 [..............................] - ETA: 0s - loss: 0.1349 - mse: 205.5135
14/45 [========>.....................] - ETA: 0s - loss: 0.1311 - mse: 193.9572
28/45 [=================>............] - ETA: 0s - loss: 0.1301 - mse: 193.5070
42/45 [===========================>..] - ETA: 0s - loss: 0.1294 - mse: 192.3850
45/45 [==============================] - 0s 4ms/step - loss: 0.1281 - mse: 191.6195

45/45 [==============================] - 0s 7ms/step - loss: 0.1281 - mse: 191.6195 - val_loss: 0.2602 - val_mse: 188.1821
Epoch 65/100

 1/45 [..............................] - ETA: 0s - loss: 0.1275 - mse: 174.6601
14/45 [========>.....................] - ETA: 0s - loss: 0.1270 - mse: 192.4588
27/45 [=================>............] - ETA: 0s - loss: 0.1230 - mse: 190.0339
41/45 [==========================>...] - ETA: 0s - loss: 0.1239 - mse: 191.8294
45/45 [==============================] - 0s 4ms/step - loss: 0.1237 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1237 - mse: 191.6196 - val_loss: 0.2857 - val_mse: 188.1821
Epoch 66/100

 1/45 [..............................] - ETA: 0s - loss: 0.1416 - mse: 196.8855
15/45 [=========>....................] - ETA: 0s - loss: 0.1250 - mse: 189.2772
28/45 [=================>............] - ETA: 0s - loss: 0.1231 - mse: 189.7699
41/45 [==========================>...] - ETA: 0s - loss: 0.1258 - mse: 191.4324
45/45 [==============================] - 0s 4ms/step - loss: 0.1257 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1257 - mse: 191.6196 - val_loss: 0.3589 - val_mse: 188.1821
Epoch 67/100

 1/45 [..............................] - ETA: 0s - loss: 0.1636 - mse: 220.4760
14/45 [========>.....................] - ETA: 0s - loss: 0.1380 - mse: 194.2081
28/45 [=================>............] - ETA: 0s - loss: 0.1409 - mse: 190.3158
41/45 [==========================>...] - ETA: 0s - loss: 0.1369 - mse: 192.0789
45/45 [==============================] - 0s 4ms/step - loss: 0.1361 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1361 - mse: 191.6196 - val_loss: 0.2906 - val_mse: 188.1821
Epoch 68/100

 1/45 [..............................] - ETA: 0s - loss: 0.0867 - mse: 191.1002
14/45 [========>.....................] - ETA: 0s - loss: 0.1203 - mse: 191.4195
27/45 [=================>............] - ETA: 0s - loss: 0.1208 - mse: 192.4287
40/45 [=========================>....] - ETA: 0s - loss: 0.1203 - mse: 191.5727
45/45 [==============================] - 0s 4ms/step - loss: 0.1199 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1199 - mse: 191.6196 - val_loss: 0.2560 - val_mse: 188.1821
Epoch 69/100

 1/45 [..............................] - ETA: 0s - loss: 0.0998 - mse: 193.2451
10/45 [=====>........................] - ETA: 0s - loss: 0.1218 - mse: 191.3234
23/45 [==============>...............] - ETA: 0s - loss: 0.1159 - mse: 191.4358
37/45 [=======================>......] - ETA: 0s - loss: 0.1160 - mse: 192.3197
45/45 [==============================] - 0s 4ms/step - loss: 0.1148 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1148 - mse: 191.6196 - val_loss: 0.3165 - val_mse: 188.1822
Epoch 70/100

 1/45 [..............................] - ETA: 0s - loss: 0.1514 - mse: 215.9775
14/45 [========>.....................] - ETA: 0s - loss: 0.1281 - mse: 189.3154
28/45 [=================>............] - ETA: 0s - loss: 0.1212 - mse: 190.1935
41/45 [==========================>...] - ETA: 0s - loss: 0.1207 - mse: 191.3980
45/45 [==============================] - 0s 4ms/step - loss: 0.1202 - mse: 191.6196

45/45 [==============================] - 0s 7ms/step - loss: 0.1202 - mse: 191.6196 - val_loss: 0.2966 - val_mse: 188.1821
Epoch 71/100

 1/45 [..............................] - ETA: 0s - loss: 0.1272 - mse: 205.6768
14/45 [========>.....................] - ETA: 0s - loss: 0.1234 - mse: 196.7356
27/45 [=================>............] - ETA: 0s - loss: 0.1133 - mse: 193.9848
41/45 [==========================>...] - ETA: 0s - loss: 0.1119 - mse: 192.5413
45/45 [==============================] - 0s 4ms/step - loss: 0.1123 - mse: 191.6197

45/45 [==============================] - 0s 7ms/step - loss: 0.1123 - mse: 191.6197 - val_loss: 0.2455 - val_mse: 188.1822
Epoch 72/100

 1/45 [..............................] - ETA: 0s - loss: 0.0991 - mse: 190.9578
15/45 [=========>....................] - ETA: 0s - loss: 0.1099 - mse: 193.2229
29/45 [==================>...........] - ETA: 0s - loss: 0.1110 - mse: 192.2650
42/45 [===========================>..] - ETA: 0s - loss: 0.1091 - mse: 192.0332
45/45 [==============================] - 0s 4ms/step - loss: 0.1085 - mse: 191.6197

45/45 [==============================] - 0s 7ms/step - loss: 0.1085 - mse: 191.6197 - val_loss: 0.2656 - val_mse: 188.1822
Epoch 73/100

 1/45 [..............................] - ETA: 0s - loss: 0.1115 - mse: 210.9371
14/45 [========>.....................] - ETA: 0s - loss: 0.1035 - mse: 195.5454
27/45 [=================>............] - ETA: 0s - loss: 0.1035 - mse: 191.6794
40/45 [=========================>....] - ETA: 0s - loss: 0.1037 - mse: 192.0590
45/45 [==============================] - 0s 4ms/step - loss: 0.1034 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1034 - mse: 191.6198 - val_loss: 0.2967 - val_mse: 188.1822
Epoch 74/100

 1/45 [..............................] - ETA: 0s - loss: 0.0834 - mse: 175.7243
14/45 [========>.....................] - ETA: 0s - loss: 0.1106 - mse: 192.4954
27/45 [=================>............] - ETA: 0s - loss: 0.1104 - mse: 190.7843
40/45 [=========================>....] - ETA: 0s - loss: 0.1105 - mse: 190.6808
45/45 [==============================] - 0s 4ms/step - loss: 0.1104 - mse: 191.6197

45/45 [==============================] - 0s 7ms/step - loss: 0.1104 - mse: 191.6197 - val_loss: 0.2210 - val_mse: 188.1822
Epoch 75/100

 1/45 [..............................] - ETA: 0s - loss: 0.0914 - mse: 180.8351
14/45 [========>.....................] - ETA: 0s - loss: 0.1069 - mse: 189.9090
28/45 [=================>............] - ETA: 0s - loss: 0.1044 - mse: 189.0691
41/45 [==========================>...] - ETA: 0s - loss: 0.1056 - mse: 191.3106
45/45 [==============================] - 0s 4ms/step - loss: 0.1054 - mse: 191.6197

45/45 [==============================] - 0s 7ms/step - loss: 0.1054 - mse: 191.6197 - val_loss: 0.2920 - val_mse: 188.1822
Epoch 76/100

 1/45 [..............................] - ETA: 0s - loss: 0.1178 - mse: 195.3140
15/45 [=========>....................] - ETA: 0s - loss: 0.1116 - mse: 193.8176
29/45 [==================>...........] - ETA: 0s - loss: 0.1084 - mse: 193.3042
43/45 [===========================>..] - ETA: 0s - loss: 0.1037 - mse: 191.3519
45/45 [==============================] - 0s 4ms/step - loss: 0.1040 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1040 - mse: 191.6198 - val_loss: 0.2756 - val_mse: 188.1823
Epoch 77/100

 1/45 [..............................] - ETA: 0s - loss: 0.0865 - mse: 195.7920
14/45 [========>.....................] - ETA: 0s - loss: 0.0977 - mse: 188.4684
27/45 [=================>............] - ETA: 0s - loss: 0.0994 - mse: 190.0693
40/45 [=========================>....] - ETA: 0s - loss: 0.1008 - mse: 191.0184
45/45 [==============================] - 0s 4ms/step - loss: 0.1023 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1023 - mse: 191.6198 - val_loss: 0.2156 - val_mse: 188.1823
Epoch 78/100

 1/45 [..............................] - ETA: 0s - loss: 0.1273 - mse: 208.8591
14/45 [========>.....................] - ETA: 0s - loss: 0.1242 - mse: 197.6013
27/45 [=================>............] - ETA: 0s - loss: 0.1124 - mse: 191.7133
41/45 [==========================>...] - ETA: 0s - loss: 0.1076 - mse: 191.4507
45/45 [==============================] - 0s 4ms/step - loss: 0.1077 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.1077 - mse: 191.6198 - val_loss: 0.3319 - val_mse: 188.1823
Epoch 79/100

 1/45 [..............................] - ETA: 0s - loss: 0.0893 - mse: 183.9606
12/45 [=======>......................] - ETA: 0s - loss: 0.0979 - mse: 190.6635
23/45 [==============>...............] - ETA: 0s - loss: 0.0996 - mse: 192.0032
36/45 [=======================>......] - ETA: 0s - loss: 0.0993 - mse: 191.9060
45/45 [==============================] - 0s 4ms/step - loss: 0.0975 - mse: 191.6198

45/45 [==============================] - 0s 8ms/step - loss: 0.0975 - mse: 191.6198 - val_loss: 0.2892 - val_mse: 188.1823
Epoch 80/100

 1/45 [..............................] - ETA: 0s - loss: 0.0593 - mse: 173.2341
14/45 [========>.....................] - ETA: 0s - loss: 0.0870 - mse: 191.0264
27/45 [=================>............] - ETA: 0s - loss: 0.0918 - mse: 191.9938
40/45 [=========================>....] - ETA: 0s - loss: 0.0929 - mse: 191.3213
45/45 [==============================] - 0s 4ms/step - loss: 0.0936 - mse: 191.6198

45/45 [==============================] - 0s 7ms/step - loss: 0.0936 - mse: 191.6198 - val_loss: 0.2440 - val_mse: 188.1823
Epoch 81/100

 1/45 [..............................] - ETA: 0s - loss: 0.0694 - mse: 183.1572
14/45 [========>.....................] - ETA: 0s - loss: 0.0887 - mse: 192.1818
27/45 [=================>............] - ETA: 0s - loss: 0.0905 - mse: 191.4551
41/45 [==========================>...] - ETA: 0s - loss: 0.0926 - mse: 191.7862
45/45 [==============================] - 0s 4ms/step - loss: 0.0926 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0926 - mse: 191.6199 - val_loss: 0.2963 - val_mse: 188.1823
Epoch 82/100

 1/45 [..............................] - ETA: 0s - loss: 0.0760 - mse: 188.2343
15/45 [=========>....................] - ETA: 0s - loss: 0.0957 - mse: 192.0853
28/45 [=================>............] - ETA: 0s - loss: 0.0932 - mse: 191.0226
42/45 [===========================>..] - ETA: 0s - loss: 0.0922 - mse: 192.3576
45/45 [==============================] - 0s 4ms/step - loss: 0.0914 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0914 - mse: 191.6199 - val_loss: 0.2894 - val_mse: 188.1824
Epoch 83/100

 1/45 [..............................] - ETA: 0s - loss: 0.0915 - mse: 195.1784
14/45 [========>.....................] - ETA: 0s - loss: 0.0839 - mse: 190.0756
27/45 [=================>............] - ETA: 0s - loss: 0.0868 - mse: 191.6145
40/45 [=========================>....] - ETA: 0s - loss: 0.0875 - mse: 191.4920
45/45 [==============================] - 0s 4ms/step - loss: 0.0872 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0872 - mse: 191.6199 - val_loss: 0.2762 - val_mse: 188.1824
Epoch 84/100

 1/45 [..............................] - ETA: 0s - loss: 0.0902 - mse: 197.5717
14/45 [========>.....................] - ETA: 0s - loss: 0.0868 - mse: 189.0859
28/45 [=================>............] - ETA: 0s - loss: 0.0897 - mse: 193.1044
41/45 [==========================>...] - ETA: 0s - loss: 0.0877 - mse: 191.7407
45/45 [==============================] - 0s 4ms/step - loss: 0.0873 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0873 - mse: 191.6199 - val_loss: 0.2484 - val_mse: 188.1824
Epoch 85/100

 1/45 [..............................] - ETA: 0s - loss: 0.0854 - mse: 195.3033
14/45 [========>.....................] - ETA: 0s - loss: 0.0846 - mse: 192.8362
28/45 [=================>............] - ETA: 0s - loss: 0.0885 - mse: 191.8641
41/45 [==========================>...] - ETA: 0s - loss: 0.0902 - mse: 191.2030
45/45 [==============================] - 0s 4ms/step - loss: 0.0908 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0908 - mse: 191.6199 - val_loss: 0.3482 - val_mse: 188.1824
Epoch 86/100

 1/45 [..............................] - ETA: 0s - loss: 0.0693 - mse: 173.2989
14/45 [========>.....................] - ETA: 0s - loss: 0.0983 - mse: 194.0628
27/45 [=================>............] - ETA: 0s - loss: 0.0927 - mse: 192.9190
40/45 [=========================>....] - ETA: 0s - loss: 0.0901 - mse: 191.8209
45/45 [==============================] - 0s 4ms/step - loss: 0.0887 - mse: 191.6200

45/45 [==============================] - 0s 8ms/step - loss: 0.0887 - mse: 191.6200 - val_loss: 0.3257 - val_mse: 188.1823
Epoch 87/100

 1/45 [..............................] - ETA: 0s - loss: 0.0882 - mse: 197.6275
14/45 [========>.....................] - ETA: 0s - loss: 0.0837 - mse: 193.8095
27/45 [=================>............] - ETA: 0s - loss: 0.0810 - mse: 190.7574
40/45 [=========================>....] - ETA: 0s - loss: 0.0831 - mse: 191.2712
45/45 [==============================] - 0s 4ms/step - loss: 0.0827 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0827 - mse: 191.6199 - val_loss: 0.3319 - val_mse: 188.1823
Epoch 88/100

 1/45 [..............................] - ETA: 0s - loss: 0.0504 - mse: 178.1816
14/45 [========>.....................] - ETA: 0s - loss: 0.0792 - mse: 191.2925
27/45 [=================>............] - ETA: 0s - loss: 0.0774 - mse: 190.9626
40/45 [=========================>....] - ETA: 0s - loss: 0.0788 - mse: 191.0738
45/45 [==============================] - 0s 4ms/step - loss: 0.0792 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0792 - mse: 191.6199 - val_loss: 0.3114 - val_mse: 188.1824
Epoch 89/100

 1/45 [..............................] - ETA: 0s - loss: 0.1174 - mse: 220.2409
13/45 [=======>......................] - ETA: 0s - loss: 0.0792 - mse: 187.0416
26/45 [================>.............] - ETA: 0s - loss: 0.0809 - mse: 189.7508
39/45 [=========================>....] - ETA: 0s - loss: 0.0802 - mse: 190.9280
45/45 [==============================] - 0s 4ms/step - loss: 0.0805 - mse: 191.6199

45/45 [==============================] - 0s 7ms/step - loss: 0.0805 - mse: 191.6199 - val_loss: 0.2863 - val_mse: 188.1824
Epoch 90/100

 1/45 [..............................] - ETA: 0s - loss: 0.1055 - mse: 213.0210
14/45 [========>.....................] - ETA: 0s - loss: 0.0806 - mse: 193.7191
27/45 [=================>............] - ETA: 0s - loss: 0.0790 - mse: 192.3447
39/45 [=========================>....] - ETA: 0s - loss: 0.0778 - mse: 191.4730
45/45 [==============================] - 0s 4ms/step - loss: 0.0766 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0766 - mse: 191.6200 - val_loss: 0.2419 - val_mse: 188.1824
Epoch 91/100

 1/45 [..............................] - ETA: 0s - loss: 0.1178 - mse: 215.5468
14/45 [========>.....................] - ETA: 0s - loss: 0.0790 - mse: 194.7396
27/45 [=================>............] - ETA: 0s - loss: 0.0797 - mse: 192.2719
40/45 [=========================>....] - ETA: 0s - loss: 0.0785 - mse: 191.8590
45/45 [==============================] - 0s 4ms/step - loss: 0.0794 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0794 - mse: 191.6200 - val_loss: 0.3420 - val_mse: 188.1824
Epoch 92/100

 1/45 [..............................] - ETA: 0s - loss: 0.0626 - mse: 192.4535
14/45 [========>.....................] - ETA: 0s - loss: 0.0868 - mse: 189.7218
27/45 [=================>............] - ETA: 0s - loss: 0.0848 - mse: 189.9768
40/45 [=========================>....] - ETA: 0s - loss: 0.0849 - mse: 190.9454
45/45 [==============================] - 0s 4ms/step - loss: 0.0843 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0843 - mse: 191.6200 - val_loss: 0.2434 - val_mse: 188.1824
Epoch 93/100

 1/45 [..............................] - ETA: 0s - loss: 0.0847 - mse: 190.1696
11/45 [======>.......................] - ETA: 0s - loss: 0.0847 - mse: 190.1158
23/45 [==============>...............] - ETA: 0s - loss: 0.0853 - mse: 191.7930
36/45 [=======================>......] - ETA: 0s - loss: 0.0810 - mse: 191.1770
45/45 [==============================] - 0s 4ms/step - loss: 0.0796 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0796 - mse: 191.6200 - val_loss: 0.3442 - val_mse: 188.1824
Epoch 94/100

 1/45 [..............................] - ETA: 0s - loss: 0.0951 - mse: 210.0542
14/45 [========>.....................] - ETA: 0s - loss: 0.0755 - mse: 190.6129
27/45 [=================>............] - ETA: 0s - loss: 0.0734 - mse: 191.5243
40/45 [=========================>....] - ETA: 0s - loss: 0.0739 - mse: 190.3051
45/45 [==============================] - 0s 4ms/step - loss: 0.0742 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0742 - mse: 191.6200 - val_loss: 0.3339 - val_mse: 188.1824
Epoch 95/100

 1/45 [..............................] - ETA: 0s - loss: 0.0538 - mse: 186.7918
14/45 [========>.....................] - ETA: 0s - loss: 0.0698 - mse: 187.1489
27/45 [=================>............] - ETA: 0s - loss: 0.0725 - mse: 190.4190
40/45 [=========================>....] - ETA: 0s - loss: 0.0732 - mse: 191.9221
45/45 [==============================] - 0s 4ms/step - loss: 0.0730 - mse: 191.6201

45/45 [==============================] - 0s 7ms/step - loss: 0.0730 - mse: 191.6201 - val_loss: 0.3654 - val_mse: 188.1824
Epoch 96/100

 1/45 [..............................] - ETA: 0s - loss: 0.0503 - mse: 171.4299
14/45 [========>.....................] - ETA: 0s - loss: 0.0667 - mse: 188.8865
28/45 [=================>............] - ETA: 0s - loss: 0.0721 - mse: 192.3252
41/45 [==========================>...] - ETA: 0s - loss: 0.0718 - mse: 191.6808
45/45 [==============================] - 0s 4ms/step - loss: 0.0722 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0722 - mse: 191.6200 - val_loss: 0.3123 - val_mse: 188.1824
Epoch 97/100

 1/45 [..............................] - ETA: 0s - loss: 0.0379 - mse: 171.6552
14/45 [========>.....................] - ETA: 0s - loss: 0.0644 - mse: 191.1909
27/45 [=================>............] - ETA: 0s - loss: 0.0693 - mse: 189.7777
40/45 [=========================>....] - ETA: 0s - loss: 0.0703 - mse: 190.6961
45/45 [==============================] - 0s 4ms/step - loss: 0.0699 - mse: 191.6201

45/45 [==============================] - 0s 7ms/step - loss: 0.0699 - mse: 191.6201 - val_loss: 0.2708 - val_mse: 188.1825
Epoch 98/100

 1/45 [..............................] - ETA: 0s - loss: 0.0740 - mse: 190.7201
15/45 [=========>....................] - ETA: 0s - loss: 0.0636 - mse: 189.2766
28/45 [=================>............] - ETA: 0s - loss: 0.0670 - mse: 191.1914
41/45 [==========================>...] - ETA: 0s - loss: 0.0690 - mse: 192.0146
45/45 [==============================] - 0s 4ms/step - loss: 0.0686 - mse: 191.6201

45/45 [==============================] - 0s 7ms/step - loss: 0.0686 - mse: 191.6201 - val_loss: 0.2711 - val_mse: 188.1824
Epoch 99/100

 1/45 [..............................] - ETA: 0s - loss: 0.0750 - mse: 175.6940
14/45 [========>.....................] - ETA: 0s - loss: 0.0784 - mse: 192.4080
27/45 [=================>............] - ETA: 0s - loss: 0.0769 - mse: 190.5115
40/45 [=========================>....] - ETA: 0s - loss: 0.0754 - mse: 191.5040
45/45 [==============================] - 0s 4ms/step - loss: 0.0744 - mse: 191.6200

45/45 [==============================] - 0s 7ms/step - loss: 0.0744 - mse: 191.6200 - val_loss: 0.3095 - val_mse: 188.1825
Epoch 100/100

 1/45 [..............................] - ETA: 0s - loss: 0.0716 - mse: 200.3689
14/45 [========>.....................] - ETA: 0s - loss: 0.0694 - mse: 193.6134
27/45 [=================>............] - ETA: 0s - loss: 0.0683 - mse: 190.9879
41/45 [==========================>...] - ETA: 0s - loss: 0.0694 - mse: 191.5620
45/45 [==============================] - 0s 4ms/step - loss: 0.0687 - mse: 191.6201

45/45 [==============================] - 0s 7ms/step - loss: 0.0687 - mse: 191.6201 - val_loss: 0.3148 - val_mse: 188.1824

predictions = bike_model %>% predict(as.matrix(new_bikes_test))

 1/34 [..............................] - ETA: 0s
34/34 [==============================] - 0s 546us/step

34/34 [==============================] - 0s 546us/step

predictions = (predictions)^2


rmse = function(x,y){
  return((mean((x - y)^2))^0.5)
}

rmse(predictions, new_bikes_test$count)

[1] 13.8597

13. Use a simple or stepwise linear regression model to predict the count. Train and test your model on the same data used to train and test your best network model. Compare the RMSE of the linear model on the test data with the RMSE of the neural network model. How does your neural network model compare to a simple linear model?

bike.lm = lm(second_bikes_train_set$count ~., data = second_bikes_train_set)

predict_bike_test <-predict(bike.lm, new_bikes_test)

Warning: prediction from a rank-deficient fit may be misleading

RMSE_bike_test <- sqrt(mean((new_bikes_test$count- predict_bike_test)^2))
RMSE_bike_test

[1] 3.51516

The simple linear model performed better than my neural network model with the RMSE of the neural network = 13.86 and the RMSE of the linear model = 3.51.